Works (95)

Updated: April 4th, 2024 10:20

2023 journal article

Group Testing With Side Information via Generalized Approximate Message Passing

IEEE TRANSACTIONS ON SIGNAL PROCESSING, 71, 2366–2375.

By: S. Cao*, R. Goenka*, C. Wong n, A. Rajwade* & D. Baron n

author keywords: Compressed sensing; contact tracing; generalized approximate message passing (GAMP); nonadaptive group testing
TL;DR: Side information (SI) collected from contact tracing (CT) is incorporated into nonadaptive/single-stage group testing algorithms based on generalized approximate message passing (GAMP) and results show that the GAMP-based algorithms provide improved accuracy. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (Web of Science; OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: July 31, 2023

2023 journal article

Rigorous State Evolution Analysis for Approximate Message Passing With Side Information

IEEE TRANSACTIONS ON INFORMATION THEORY, 69(6), 3989–4013.

By: H. Liu n, C. Rush* & D. Baron n

author keywords: Channel estimation; Noise measurement; Task analysis; Message passing; Testing; Predictive models; Estimation; Approximate message passing (AMP); compressed sensing; side information (SI); state evolution (SE)
TL;DR: This work provides rigorous performance guarantees for AMP-SI when there are statistical dependencies between the signal and SI pairs and the entries of the measurement matrix are independent and identically distributed (i.i.d.) Gaussian. (via Semantic Scholar)
Sources: ORCID, Web Of Science, NC State University Libraries
Added: November 10, 2022

2023 article

Thermal Estimation for 3D-ICs through Generative Networks

2023 IEEE INTERNATIONAL 3D SYSTEMS INTEGRATION CONFERENCE, 3DIC.

By: P. Kashyap n, P. Ravichandiran n, L. Wang*, D. Baron n, C. Wong n, T. Wu n, P. Franzon n

author keywords: 3DIC; thermal; generative; GAN; hybrid-bonding
TL;DR: This paper presents a generative approach for modeling the power to heat dissipation for a 3DIC and shows that, given the power map, the model can generate the resultant heat for the bulk, opening the door for thermally aware floorplanning. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: August 14, 2023

2022 article

Mismatched Estimation in the Distance Geometry Problem

2022 56TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS, pp. 1031–1035.

By: M. Abdelkhalek n, D. Baron n & C. Wong n

TL;DR: This paper argues that more accurate estimates can be obtained when an estimation procedure that uses the correct likelihood function of noisy measurements is performed, and demonstrates that least-squares estimates could be suboptimal by several dB. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: June 5, 2023

2022 article

Modeling of Adaptive Receiver Performance Using Generative Adversarial Networks

IEEE 72ND ELECTRONIC COMPONENTS AND TECHNOLOGY CONFERENCE (ECTC 2022), pp. 1958–1963.

By: P. Kashyap n, Y. Choi*, S. Dey*, D. Baron n, C. Wong n, T. Wu n, C. Cheng*, P. Franzon n

author keywords: SerDes; receiver; behavior modeling; adaptive; generative; GAN; DFE; IBIS-AMI
TL;DR: A data-driven approach to modeling a high-speed serializer/deserializer (SerDes) receiver through generative adversarial networks (GANs) through the use of a discriminator structure that improves the training to generate a contour plot that makes it difficult to distinguish the ground truth. (via Semantic Scholar)
UN Sustainable Development Goal Categories
10. Reduced Inequalities (OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: September 19, 2022

2022 article

RxGAN: Modeling High-Speed Receiver through Generative Adversarial Networks

MLCAD '22: PROCEEDINGS OF THE 2022 ACM/IEEE 4TH WORKSHOP ON MACHINE LEARNING FOR CAD (MLCAD), pp. 167–172.

By: P. Kashyap n, A. Gajjar n, Y. Choi*, C. Wong n, D. Baron n, T. Wu n, C. Cheng*, P. Franzon n

Contributors: P. Kashyap n

author keywords: SerDes; receiver; behavior modeling; adaptive; generative; measurement; GAN; DFE; IBIS-AMI
TL;DR: This work proposes a data-driven approach using generative adversarial training to model a real-world receiver with varying DFE and CTLE configurations while handling different channel conditions and bitstreams. (via Semantic Scholar)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy (OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: October 31, 2022

2021 article

CONTACT TRACING ENHANCES THE EFFICIENCY OF COVID-19 GROUP TESTING

2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021), pp. 8168–8172.

By: R. Goenka, S. Cao, C. Wong*, A. Rajwade & D. Baron*

author keywords: Contact tracing; nonadaptive group testing; compressed sensing; overlapping group LASSO; generalized approximate message passing (GAMP)
TL;DR: This work uses side information (SI) collected from contact tracing (CT) within nonadaptive/single-stage group testing algorithms to explore and demonstrate how CT SI can further improve group testing performance. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: November 29, 2021

2021 article

High Speed Receiver Modeling Using Generative Adversarial Networks

IEEE 30TH CONFERENCE ON ELECTRICAL PERFORMANCE OF ELECTRONIC PACKAGING AND SYSTEMS (EPEPS 2021).

By: P. Kashyap n, W. Pitts n, D. Baron n, C. Wong n, T. Wu n & P. Franzon n

author keywords: eye diagram; IBIS-AMI; generative model; generative adversarial network; GAN; receiver
TL;DR: The model is not built with domain knowledge but learned from a wide range of channel conditions and input bitstreams to generate an eye diagram, and a neural network model is developed to evaluate the generated eye diagram's relevant characteristics, such as eye height and width. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, NC State University Libraries
Added: March 21, 2022

2021 article

Local Convergence of an AMP Variant to the LASSO Solution in Finite Dimensions

2021 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT), pp. 2256–2261.

By: Y. Ma*, M. Kang n, J. Silversteint & D. Baron n

TL;DR: It is shown that whenever the AMP variant converges, it converges to the LASSO solution for arbitrary finite dimensional regression matrices and that the original AMP, which is a special case of the proposed AMP variants, is locally stable around the LassO solution. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: October 26, 2021

2019 journal article

An Approximate Message Passing Framework for Side Information

IEEE TRANSACTIONS ON SIGNAL PROCESSING, 67(7), 1875–1888.

By: A. Ma*, Y. Zhou n, C. Rush*, D. Baron n & D. Needell*

author keywords: Approximate message passing; side information; sparse signal recovery
TL;DR: This paper develops a suite of algorithms, called AMP-SI, and derive denoisers for the BDD and BG models, and demonstrates the simplicity and applicability of this approach. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: March 25, 2019

2019 article

Analysis of Approximate Message Passing With Non-Separable Denoisers and Markov Random Field Priors

Ma, Y., Rush, C., & Baron, D. (2019, November). IEEE TRANSACTIONS ON INFORMATION THEORY, Vol. 65, pp. 7367–7389.

By: Y. Ma n, C. Rush* & D. Baron n

author keywords: Approximation algorithms; Task analysis; Approximate message passing; non-separable denoiser; Markov random field; finite sample analysis
TL;DR: A rigorous analysis of the performance of AMP is provided, demonstrating the accuracy of the state evolution predictions, when a class of non-separable sliding-window denoisers is applied. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: February 3, 2020

2018 journal article

Performance Limits With Additive Error Metrics in Noisy Multimeasurement Vector Problems

IEEE TRANSACTIONS ON SIGNAL PROCESSING, 66(20), 5338–5348.

By: J. Zhu* & D. Baron n

author keywords: Active user detection; error metric; message passing; multi-measurement vector problem
TL;DR: This work proposes a novel setup for active user detection in multiuser communication and demonstrates the promise of the proposed setup, and proposes a message passing algorithmic framework that achieves the optimal performance of the algorithm. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: October 16, 2018

2017 conference paper

An overview of multi-processor approximate message passing

2017 51st Annual Conference on Information Sciences and Systems (CISS). Presented at the 2017 51st Annual Conference on Information Sciences and Systems (CISS).

By: J. Zhu*, R. Pilgrim* & D. Baron n

Event: 2017 51st Annual Conference on Information Sciences and Systems (CISS)

TL;DR: An overview of two multi-processor versions of AMP, where each computing node stores a subset of the rows of the matrix and processes corresponding measurements, and the use of data compression to reduce communication in the MP network is highlighted. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 9, 2019

2017 conference paper

Analysis of approximate message passing with a class of non-separable denoisers

2017 ieee international symposium on information theory (isit), 231–235.

By: Y. Ma n, C. Rush* & D. Baron n

TL;DR: It is proved that a new form of state evolution still accurately predicts AMP performance, using a class of non-separable sliding-window denoisers, which will lead to a characterization of more general denoiser in problems including compressive image reconstruction. (via Semantic Scholar)
Sources: NC State University Libraries, NC State University Libraries
Added: August 6, 2018

2017 conference paper

Conditional approximate message passing with side information

2017 51st Asilomar Conference on Signals, Systems, and Computers. Presented at the 2017 51st Asilomar Conference on Signals, Systems, and Computers.

By: D. Baron n, A. Ma, D. Needell, C. Rush & T. Woolf

Event: 2017 51st Asilomar Conference on Signals, Systems, and Computers

TL;DR: This work lays the framework for a class of Bayes-optimal signal recovery algorithms referred to as conditional approximate message passing (CAMP) that make use of available SI. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 9, 2019

2017 conference paper

Generalized geometric programming for rate allocation in consensus

2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton). Presented at the 2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

By: R. Pilgrim n, J. Zhu n, D. Baron n & W. Bajwa*

Event: 2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

TL;DR: This work shows for Gaussian-distributed initial states with entropy-coded scalar quantization and vector quantization that the coding rates for distributed averaging can be optimized through generalized geometric programming, and motivates the incorporation of side-information through differential or predictive coding to improve rate-distortion performance. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 9, 2019

2017 conference paper

Multiprocessor approximate message passing with column-wise partitioning

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Presented at the 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

By: Y. Ma n, Y. Lu* & D. Baron n

Event: 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

TL;DR: This paper shows that column-wise multiprocessor AMP (C-MP-AMP) obeys an SE under the same assumptions when the SE for AMP holds, and shows that damping can improve the convergence performance of C- MP-AMP. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 9, 2019

2017 journal article

Performance Limits for Noisy Multimeasurement Vector Problems

IEEE TRANSACTIONS ON SIGNAL PROCESSING, 65(9), 2444–2454.

By: J. Zhu n, D. Baron n & F. Krzakala*

author keywords: Approximate message passing; multimeasurement vector problem; replica analysis
TL;DR: Numerical results illustrate that more signal vectors in the jointly sparse signal ensemble lead to a better phase transition, and the MMSE's of complex CS problems with both real and complex measurement matrices are also analyzed. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2016 journal article

Approximate Message Passing Algorithm With Universal Denoising and Gaussian Mixture Learning

IEEE Transactions on Signal Processing, 64(21), 5611–5622.

By: Y. Ma n, J. Zhu n & D. Baron n

author keywords: Approximate message passing; compressed sensing; Gaussian mixture model; universal denoising
TL;DR: A novel algorithmic framework that combines the approximate message passing CS reconstruction framework with a universal denoising scheme based on context quantization, and provides two implementations of the universal CS recovery algorithm with one being faster and the other being more accurate. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 9, 2019

2016 journal article

Compressive Hyperspectral Imaging via Approximate Message Passing

IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 10(2), 389–401.

By: J. Tan n, Y. Ma n, H. Rueda*, D. Baron n & G. Arce*

author keywords: Approximate message passing; CASSI; compressive hyperspectral imaging; gradient projection for sparse reconstruction; image denoising; two-step iterative shrinkage/thresholding; Wiener filtering
TL;DR: The adaptive Wiener filter is modified and employed to solve for the divergence issue of AMP, and the numerical experiments show that AMP-3D-Wiener outperforms existing widely-used algorithms such as gradient projection for sparse reconstruction (GPSR) and two-step iterative shrinkage/thresholding (TwIST) given a similar amount of runtime. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2016 conference paper

Multi-processor approximate message passing using lossy compression

International conference on acoustics speech and signal processing, 6240–6244.

By: P. Han*, J. Zhu n, R. Niu* & D. Baron n

TL;DR: A communication-efficient multi-processor compressed sensing framework based on the approximate message passing algorithm is proposed, which performs lossy compression on the data being communicated between processors, resulting in a reduction in communication costs with a minor degradation in recovery quality. (via Semantic Scholar)
Sources: NC State University Libraries, NC State University Libraries
Added: August 6, 2018

2016 conference paper

Performance trade-offs in multi-processor approximate message passing

2016 ieee international symposium on information theory, 680–684.

By: J. Zhu n, A. Beirami* & D. Baron n

TL;DR: It is proved that the achievable region of this MOP is convex, and conjecture how the combined cost of computation and communication scales with the desired mean squared error. (via Semantic Scholar)
Sources: NC State University Libraries, NC State University Libraries
Added: August 6, 2018

2015 journal article

A Universal Parallel Two-Pass MDL Context Tree Compression Algorithm

IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 9(4), 741–748.

By: N. Krishnan n & D. Baron n

author keywords: Big data; computational complexity; data compression; distributed computing; minimum description length; parallel algorithms; redundancy; two-pass code; universal compression; work-efficient algorithms
TL;DR: A novel lossless universal data compression algorithm that uses parallel computational units to increase the throughput and improves the compression by using different quantizers for states of the context tree based on the number of symbols corresponding to those states. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2015 conference paper

Approximate message passing in coded aperture snapshot spectral imaging

2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP). Presented at the 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

By: J. Tan n, Y. Ma n, H. Rueda*, D. Baron n & G. Arce*

Event: 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP)

TL;DR: The simulation results show that AMP-3D-Wiener outperforms existing widely-used algorithms such as gradient projection for sparse reconstruction (GPSR) and two-step iterative shrinkage/thresholding (TwIST) given the same amount of runtime. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 9, 2019

2015 journal article

Compressive Imaging via Approximate Message Passing With Image Denoising

IEEE Transactions on Signal Processing, 63(8), 2085–2092.

By: J. Tan n, Y. Ma n & D. Baron n

author keywords: Approximate message passing; compressive imaging; image denoising; wavelet transform
TL;DR: Compressive imaging algorithms that employ the approximate message passing (AMP) framework are proposed that significantly improve over the state of the art in terms of both reconstruction error and runtime. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 9, 2019

2015 journal article

Creating Analytic Online Homework for Digital Signal Processing [sp Education]

IEEE Signal Processing Magazine, 32(5), 112–118.

By: H. Trussell n & D. Baron n

TL;DR: An article by W.L. Everitt in the 1962 50th anniversary issue of Proceedings of the IEEE, "Engineering Education"-Circa 2012 A.D.," predicted that, in the future, training will be done primarily with computers, remarking, "Relieved of the necessity of spending most of their time on the training function, devoted teachers will be able to concentrate their efforts on 'education'. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Sources: Crossref, NC State University Libraries, Web Of Science
Added: August 6, 2018

2015 conference paper

Mismatched estimation in large linear systems

2015 ieee international symposium on information theory (isit), 760–764.

By: Y. Ma n, D. Baron n & A. Beirami*

TL;DR: This work focuses on large linear systems where the measurements are acquired via an independent and identically distributed random matrix, and are corrupted by additive white Gaussian noise. (via Semantic Scholar)
Sources: NC State University Libraries, NC State University Libraries
Added: August 6, 2018

2015 journal article

Recovery From Linear Measurements With Complexity-Matching Universal Signal Estimation

IEEE TRANSACTIONS ON SIGNAL PROCESSING, 63(6), 1512–1527.

By: J. Zhu n, D. Baron n & M. Duarte*

author keywords: Compressed sensing; MAP estimation; Markov chain Monte Carlo; universal algorithms
TL;DR: This paper considers universal CS recovery, where the statistics of a stationary ergodic signal source are estimated simultaneously with the signal itself, and focuses on a maximum a posteriori (MAP) estimation framework that leverages universal priors to match the complexity of the source. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2014 conference paper

A Parallel two-pass MDL context tree algorithm for universal source coding

2014 ieee international symposium on information theory (isit), 1862–1865.

By: N. Krishnan*, D. Baron* & M. Mihcak n

TL;DR: A novel lossless universal source coding algorithm that uses parallel computational units to increase the throughput and redundancy and is work-efficient, i.e., its computational complexity is O(N=B). (via Semantic Scholar)
Sources: NC State University Libraries, NC State University Libraries
Added: August 6, 2018

2014 conference paper

Complexity-adaptive universal signal estimation for compressed sensing

2014 IEEE Workshop on Statistical Signal Processing (SSP), 388–391.

By: J. Zhu n, D. Baron n & M. Duarte*

TL;DR: This paper significantly improves on previous work, especially for continuous-valued signals, by offering a four-stage algorithm called Complexity-Adaptive Universal Signal Estimation (CAUSE), where the alphabet size of the estimate adaptively matches the coding complexity of the signal. (via Semantic Scholar)
Sources: NC State University Libraries, NC State University Libraries
Added: August 6, 2018

2014 conference paper

Compressed Sensing via Universal Denoising and Approximate Message Passing

Proc. 52d Allerton Conference on Communication, Control, and Computing. Monticello, IL.

By: Y. Ma, J. Zhu & D. Baron

Source: NC State University Libraries
Added: March 9, 2019

2014 conference paper

Compressive imaging via approximate message passing with wavelet-based image denoising

2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP). Presented at the 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

By: J. Tan n, Y. Ma n & D. Baron n

Event: 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)

TL;DR: This work applies an adaptive Wiener filter, which is a wavelet-based image denoiser, within AMP, to improve over current state of the art compressive imaging algorithms in terms of both reconstruction error and runtime. (via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities (OpenAlex)
Sources: Crossref, NC State University Libraries
Added: March 9, 2019

2014 journal article

Empirical Bayes and Full Bayes for Signal Estimation

ArXiv:1405.2113 [Cs, Math]. http://arxiv.org/abs/1405.2113

By: Y. Ma, J. Tan, N. Krishnan & D. Baron

Source: NC State University Libraries
Added: March 9, 2019

2014 conference paper

Performance of parallel two-pass MDL context tree algorithm

2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP). Presented at the 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

By: N. Krishnan n & D. Baron n

Event: 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)

TL;DR: Numerical results from a prototype implementation suggest that the proposed algorithm offers a better trade-off between compression and throughput than competing universal data compression algorithms. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 9, 2019

2014 journal article

Signal Estimation With Additive Error Metrics in Compressed Sensing

IEEE TRANSACTIONS ON INFORMATION THEORY, 60(1), 150–158.

By: J. Tan n, D. Carmon & D. Baron n

author keywords: Belief propagation (BP); compressed sensing; error metric; estimation theory
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2014 conference paper

Signal estimation with low infinity-norm error by minimizing the mean p-norm error

2014 48th Annual Conference on Information Sciences and Systems (CISS).

By: J. Tan n, D. Baron n & L. Dai*

TL;DR: Numerical results show that the ℓp-norm minimizer outperforms the Wiener filter, and suggest that the optimal value of p increases with the signal dimension, and that for i.i.d. Bernoulli-Gaussian input signals, the optimal p increaseswith the percentage of nonzeros. (via Semantic Scholar)
Sources: NC State University Libraries, NC State University Libraries
Added: August 6, 2018

2014 journal article

Two-Part Reconstruction With Noisy-Sudocodes

IEEE TRANSACTIONS ON SIGNAL PROCESSING, 62(23), 6323–6334.

By: Y. Ma n, D. Baron n & D. Needell*

author keywords: Compressed sensing; two-part reconstruction; 1-bit CS
TL;DR: This work proposes a Noisy-Sudocodes algorithm that performs two-part reconstruction of sparse signals in the presence of measurement noise and provides a theoretical analysis that characterizes the trade-off between runtime and reconstruction quality. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2014 journal article

Wiener Filters in Gaussian Mixture Signal Estimation With l(infinity)-Norm Error

IEEE TRANSACTIONS ON INFORMATION THEORY, 60(10), 6626–6635.

By: J. Tan n, D. Baron n & L. Dai*

author keywords: Estimation theory; Gaussian mixtures; l(infinity)-norm error; linear mixing systems; parallel Gaussian channels; Wiener filters
TL;DR: It is proved that, in an asymptotic setting where the signal dimension N → ∞, the l∞-norm error always comes from the Gaussian component that has the largest variance, and the Wiener filter asymPTotically achieves the optimal expected l ∼norm error. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2013 journal article

Measurement Bounds for Sparse Signal Ensembles via Graphical Models

IEEE Transactions on Information Theory, 59(7), 4280–4289.

By: M. Duarte*, M. Wakin*, D. Baron n, S. Sarvotham* & R. Baraniuk*

author keywords: Compressive sensing (CS); random projections; signal ensembles; sparsity
TL;DR: This paper introduces an ensemble sparsity model for capturing the intra- and inter-signal correlations within a collection of sparse signals and describes the fundamental number of noiseless measurements that each sensor must collect to ensure that the signals are jointly recoverable. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 9, 2019

2013 conference paper

Performance regions in compressed sensing from noisy measurements

2013 47th Annual Conference on Information Sciences and Systems (CISS).

By: J. Zhu n & D. Baron n

TL;DR: It is shown that in several regions, which have different measurement rates and noise levels, the reconstruction error behaves differently, and it may be possible to develop reconstruction algorithms with lower error in that region. (via Semantic Scholar)
Sources: NC State University Libraries, NC State University Libraries
Added: August 6, 2018

2013 conference paper

Signal reconstruction in linear mixing systems with different error metrics

2013 Information Theory and Applications Workshop (ITA).

By: J. Tan n & D. Baron n

TL;DR: A simple, fast, and highly general algorithm that reconstructs the signal by minimizing the user-defined error metric and can be adjusted to minimize the ℓ∞ error, which is not additive. (via Semantic Scholar)
Sources: NC State University Libraries, NC State University Libraries
Added: August 6, 2018

2012 journal article

An MCMC Approach to Universal Lossy Compression of Analog Sources

IEEE TRANSACTIONS ON SIGNAL PROCESSING, 60(10), 5230–5240.

By: D. Baron n & T. Weissman*

author keywords: Compression algorithms; rate distortion; simulated annealing
TL;DR: A lossy compression algorithm for analog sources that relies on a finite reproduction alphabet that achieves, in an appropriate asymptotic sense, the optimum Shannon theoretic tradeoff between rate and distortion, universally for stationary ergodic continuous amplitude sources. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2012 conference paper

Optimal estimation with arbitrary error metrics in compressed sensing

2012 IEEE Statistical Signal Processing Workshop (ssp), 588–591.

By: J. Tan n, D. Carmon n & D. Baron n

TL;DR: This paper proposes a simple, fast, and general algorithm that estimates the original signal by minimizing an arbitrary error metric defined by the user, and describes a general method to compute the fundamental information-theoretic performance limit for any well-defined error metric. (via Semantic Scholar)
Sources: NC State University Libraries, NC State University Libraries
Added: August 6, 2018

2012 journal article

Variable Length Compression of Codeword Indices for Lossy Compression

IEEE SIGNAL PROCESSING LETTERS, 19(12), 849–852.

By: D. Baron* & T. Jacob*

author keywords: Entropy coding; lossy compression; rate distortion; variable length coding
TL;DR: It is illustrated that variable length coding yields a reduction in the rate over fixed length coding, and allows to reach a requisite rate distortion performance level using a smaller codebook. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2011 journal article

Fault Identification Via Nonparametric Belief Propagation

IEEE TRANSACTIONS ON SIGNAL PROCESSING, 59(6), 2602–2613.

By: D. Bickson*, D. Baron n, A. Ihler*, H. Avissar* & D. Dolev*

author keywords: Compressed sensing (CS); fault identification; message passing; nonparametric belief propagation (NBP); stochastic approximation
TL;DR: It is shown empirically that the nonparametric belief propagation solver is more accurate than recent state-of-the-art algorithms including interior point methods and semidefinite programming. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2011 conference paper

Information complexity and estimation

Fourth Workshop Inf. Theoretic Methods Science Eng. Presented at the WITMSE 2011.

By: D. Baron

Event: WITMSE 2011

Source: NC State University Libraries
Added: March 9, 2019

2011 conference paper

Universal MAP estimation in compressed sensing

2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton). Presented at the 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

By: D. Baron n & M. Duarte*

Event: 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

TL;DR: This paper provides initial theoretical, algorithmic, and experimental evidence based on maximum a posteriori (MAP) estimation that shows the promise of universality in CS, particularly for low-complexity sources that do not exhibit standard sparsity or compressibility. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 9, 2019

2010 conference paper

An MCMC Approach to Lossy Compression of Continuous Sources

2010 Data Compression Conference. Presented at the 2010 Data Compression Conference.

By: D. Baron* & T. Weissman*

Event: 2010 Data Compression Conference

author keywords: Lossy compression; rate distortion theory; stationary ergodic sources; universal compression
TL;DR: This work proposes a lossy compression algorithm for continuous amplitude sources that relies on a finite reproduction alphabet that grows with the input length, and proposes an MCMC-based algorithm that uses a (smaller) adaptive reproduction alphabet. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 9, 2019

2010 journal article

Bayesian Compressive Sensing Via Belief Propagation

IEEE Transactions on Signal Processing, 58(1), 269–280.

By: D. Baron*, S. Sarvotham* & R. Baraniuk*

author keywords: Bayesian inference; belief propagation; compressive sensing; fast algorithms; sparse matrices
TL;DR: This work performs asymptotically optimal Bayesian inference using belief propagation (BP) decoding, which represents the CS encoding matrix as a graphical model, and focuses on a two-state mixture Gaussian model that is easily adapted to other signal models. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 9, 2019

2009 conference paper

A single-letter characterization of optimal noisy compressed sensing

2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton). Presented at the 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton 2009).

By: D. Guo*, D. Baron* & S. Shamai*

Event: 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton 2009)

TL;DR: Using the replica method, the outcome of inferring about any fixed collection of signal elements is shown to be asymptotically decoupled, and the single-letter characterization is rigorously justified in the special case of sparse measurement matrices where belief propagation becomes asymPTotically optimal. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 9, 2019

2009 report

Distributed Compressive Sensing

By: D. Baron*, M. Duarte, M. Wakin, S. Sarvotham & R. Baraniuk

TL;DR: A new theory for distributed compressive sensing (DCS) is introduced that enables new distributed coding algorithms for multi-signal ensembles that exploit both intra- and inter-signal correlation structures. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 23, 2019

2009 journal article

Representation and Compression of Multidimensional Piecewise Functions Using Surflets

IEEE Transactions on Information Theory, 55(1), 374–400.

By: V. Chandrasekaran*, M. Wakin*, D. Baron* & R. Baraniuk*

author keywords: Compression; discontinuities; metric entropy; multidimensional signals; multiscale representations; nonlinear approximation; rate-distortion; sparse representations; surflets; wavelets
TL;DR: Simulation results on synthetic signals provide a comparison between surflet-based coders and previously studied approximation schemes based on wedgelets and wavelets, and a new scale-adaptive dictionary that contains few elements at coarse and fine scales, but many elements at medium scales is proposed. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 9, 2019

2008 conference paper

Performance Limits for Jointly Sparse Signals via Graphical Models

Proceedings of Sensor, Signal, and Information Processing Workshop. Presented at the SenSIP.

By: M. Duarte, S. Sarvotham, D. Baron, M. Wakin & R. Baraniuk

Event: SenSIP

Source: NC State University Libraries
Added: March 23, 2019

2008 conference paper

The secrecy of compressed sensing measurements

2008 46th Annual Allerton Conference on Communication, Control, and Computing. Presented at the 2008 46th Annual Allerton Conference on Communication, Control, and Computing.

By: Y. Rachlin* & D. Baron*

Event: 2008 46th Annual Allerton Conference on Communication, Control, and Computing

TL;DR: It is demonstrated that compressed sensing-based encryption does not achieve Shannon's definition of perfect secrecy, but can provide a computational guarantee of secrecy. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 18, 2019

2008 report

Theoretical Performace Limits for Jointly Sparse Signals via Graphical Models

(Technical Report No. ECE-0802). Electrical and Computer Engineering Department, Rice University.

By: M. Duarte, S. Sarvotham, M. Wakin, D. Baron & R. Baraniuk

Source: NC State University Libraries
Added: March 24, 2019

2006 conference paper

A new compressive imaging camera architecture using optical-domain compression

In C. A. Bouman, E. L. Miller, & I. Pollak (Eds.), Computational Imaging IV.

By: D. Takhar*, J. Laska*, M. Wakin*, M. Duarte*, D. Baron*, S. Sarvotham*, K. Kelly*, R. Baraniuk*

Ed(s): C. Bouman, E. Miller & I. Pollak

Event: Electronic Imaging 2006

author keywords: Compressed Sensing; sparsity; incoherent projections; random matrices; linear programming; imaging; camera
TL;DR: A new camera architecture is developed that employs a digital micromirror array to perform optical calculations of linear projections of an image onto pseudorandom binary patterns that can be adapted to image at wavelengths that are currently impossible with conventional CCD and CMOS imagers. (via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities (OpenAlex)
Sources: Crossref, NC State University Libraries
Added: March 22, 2019

2006 conference paper

An Architecture for Compressive Imaging

2006 International Conference on Image Processing. Presented at the 2006 International Conference on Image Processing.

By: M. Wakin*, J. Laska*, M. Duarte*, D. Baron*, S. Sarvotham*, D. Takhar*, K. Kelly*, R. Baraniuk*

Event: 2006 International Conference on Image Processing

author keywords: data acquisition; data compression; image coding; image sensors; video coding
TL;DR: This paper proposes algorithms and hardware to support a new theory of compressive imaging based on a new digital image/video camera that directly acquires random projections of the signal without first collecting the pixels/voxels. (via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities (OpenAlex)
Sources: Crossref, NC State University Libraries
Added: March 18, 2019

2006 conference paper

Analog-to-Information Conversion via Random Demodulation

2006 IEEE Dallas/CAS Workshop on Design, Applications, Integration and Software. Presented at the 2006 IEEE Dallas/CAS Workshop on Design, Applications, Integration and Software.

By: S. Kirolos*, J. Laska*, M. Wakin*, M. Duarte*, D. Baron*, T. Ragheb*, Y. Massoud*, R. Baraniuk*

Event: 2006 IEEE Dallas/CAS Workshop on Design, Applications, Integration and Software

TL;DR: This paper proposes a system that uses modulation, filtering, and sampling to produce a low-rate set of digital measurements, inspired by the theory of compressive sensing (CS), which states that a discrete signal having a sparse representation in some dictionary can be recovered from a small number of linear projections of that signal. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 18, 2019

2006 conference paper

Coding vs. Packet Retransmission over Noisy Channels

2006 40th Annual Conference on Information Sciences and Systems. Presented at the 2006 40th Annual Conference on Information Sciences and Systems.

By: D. Baron*, S. Sarvotham* & R. Baraniuk*

Event: 2006 40th Annual Conference on Information Sciences and Systems

author keywords: channel coding; cross-layer design; non-asymptotic information theory; packet networks; piecewise memoryless channels; universal channel coding
Sources: Crossref, NC State University Libraries
Added: March 18, 2019

2006 report

Compressed Sensing Reconstruction via Belief Propagation

(Technical Report No. ECE-0601). Electrical and Computer Engineering Department, Rice University.

By: S. Sarvotham, D. Baron & R. Baraniuk

Source: NC State University Libraries
Added: March 24, 2019

2006 conference paper

Compressive Imaging for Video Representation and Coding

Proceedings of Picture Coding Symposium. Presented at the PCS.

By: M. Wakin, J. Laska, M. Duarte, D. Baron, S. Sarvotham, D. Takhar, K. Kelly, R. Baraniuk

Event: PCS

Source: NC State University Libraries
Added: March 24, 2019

2006 conference paper

Distributed Compressed Sensing of Jointly Sparse Signals

Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005. Presented at the Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005.

By: M. Duarte*, S. Sarvotham*, D. Baron*, M. Wakin* & R. Baraniuk*

Event: Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005.

TL;DR: This paper presents a second new model for jointly sparse signals that allows for joint recovery of multi- ple signals from incoherent projections through simultane- ous greedy pursuit algorithms and characterize the number of measurements per sensor required for accurate reconstruction. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 23, 2019

2006 journal article

Faster sequential universal coding via block partitioning

IEEE Transactions on Information Theory, 52(4), 1708–1710.

By: D. Baron* & R. Baraniuk*

author keywords: lossless source coding; redundancy; sequential coding; universal coding
TL;DR: The redundancy with the approach is greater than with Rissanen's block partitioning scheme by a multiplicative factor 1+O(1/log(log(n))), hence it asymptotically approaches the entropy at the fastest possible rate. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 20, 2019

2006 conference paper

Measurements vs. Bits: Compressed Sensing meets Information Theory

Proceedings of 44th Allerton Conference on Communication, Control, and Computing. Monticello, IL.

By: S. Sarvotham, D. Baron & R. Baraniuk

Source: NC State University Libraries
Added: March 23, 2019

2006 conference paper

Random Filters for Compressive Sampling and Reconstruction

2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings. Presented at the 2006 IEEE International Conference on Acoustics Speed and Signal Processing.

Event: 2006 IEEE International Conference on Acoustics Speed and Signal Processing

TL;DR: A new technique for efficiently acquiring and reconstructing signals based on convolution with a fixed FIR filter having random taps, which is sufficiently generic to summarize many types of compressible signals and generalizes to streaming and continuous-time signals. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 23, 2019

2006 conference paper

Sudocodes – Fast Measurement and Reconstruction of Sparse Signals

2006 IEEE International Symposium on Information Theory. Presented at the 2006 IEEE International Symposium on Information Theory.

By: S. Sarvotham*, D. Baron* & R. Baraniuk*

Event: 2006 IEEE International Symposium on Information Theory

TL;DR: This work proposes a non-adaptive construction of a sparse Phi comprising only the values 0 and 1; hence the computation of y involves only sums of subsets of the elements of x. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: April 11, 2019

2006 conference paper

Universal distributed sensing via random projections

2006 5th International Conference on Information Processing in Sensor Networks. Presented at the The Fifth International Conference on Information Processing in Sensor Networks.

By: M. Duarte*, M. Wakin*, D. Baron* & R. Baraniuk*

Event: The Fifth International Conference on Information Processing in Sensor Networks

Sources: Crossref, NC State University Libraries
Added: March 18, 2019

2006 conference paper

Variable-Rate Universal Slepian-Wolf Coding with Feedback

Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005. Presented at the Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005.

By: S. Sarvotham*, D. Baron* & R. Baraniuk*

Event: Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005.

TL;DR: A universal scheme for Slepian-Wolf coding that allows encoding at variable rates close to the Slepan-Wolf limit and shows that the redundancy of the scheme is O(radicnPhi-1(isin) bits over the SlePian- Wolf limit. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 23, 2019

2005 conference paper

An Information-Theoretic Approach to Distributed Compressed Sensing

Proceedings of 43d Allerton Conference on Communication, Control, and Computing. Monticello, IL.

By: D. Baron, M. Duarte, S. Sarvotham, M. Wakin & R. Baraniuk

Source: NC State University Libraries
Added: March 24, 2019

2005 report

Analysis of the DCS One-Stage Greedy Algorithm for Common Sparse Supports

(Technical Report No. ECE-05-03). Electrical and Computer Engineering Department, Rice University.

By: S. Sarvotham, M. Wakin, D. Baron, M. Duarte & R. Baraniuk

Source: NC State University Libraries
Added: March 24, 2019

2005 journal article

Antisequential Suffix Sorting for BWT-Based Data Compression

IEEE Transactions on Computers, 54(4), 385–397.

By: D. Baron* & Y. Bresler*

author keywords: Burrows Wheeler transform; data compression; source coding; suffix sorting; VLSI
TL;DR: A new suffix lists data structure is proposed that leads to three fast, antisequential, and memory-efficient algorithms for suffix sorting that could accelerate suffix sorting by at least an order of magnitude and enable high-speed BWT-based compression systems. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 20, 2019

2005 conference paper

How quickly can we approach channel capacity?

Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004. Presented at the Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004.

By: D. Baron*, M. Khojastepour* & R. Baraniuk*

Event: Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004.

TL;DR: The nonasymptotic capacity C/sub NA/(n, /spl epsi/) is defined as the maximal rate of codebooks that achieve a probability of codeword error while using codewords of length n to address the channel capacity C. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 23, 2019

2005 conference paper

Joint Sparsity Models for Distributed Compressed Sensing

Online Proceedings of the Workshop on Signal Processing with Adaptive Sparse Structured Representations. Presented at the SPARS.

By: M. Duarte, S. Sarvotham, M. Wakin, D. Baron & R. Baraniuk

Event: SPARS

Source: NC State University Libraries
Added: March 24, 2019

2005 conference paper

Non-Asymptotic Performance of Symmetric Slepian-Wolf Coding

Proceedings of 39th Annual Conference on Information Sciences and Systems. Presented at the CISS 2005.

By: S. Sarvotham, D. Baron & R. Baraniuk

Event: CISS 2005

Source: NC State University Libraries
Added: March 24, 2019

2005 conference paper

Recovery of Jointly Sparse Signals from Few Random Projections

Proceedings of Workshop on Neural Information Processing Systems. Vancouver, Canada.

By: M. Wakin, S. Sarvotham, M. Duarte, D. Baron & R. Baraniuk

Source: NC State University Libraries
Added: March 24, 2019

2005 conference paper

Variable-Rate Coding with Feedback for Universal Communication Systems

Proceedings of 43d Allerton Conference on Communication, Control, and Computing. Monticello, IL.

By: S. Sarvotham, D. Baron & R. Baraniuk

Source: NC State University Libraries
Added: March 24, 2019

2004 journal article

An O(N) Semipredictive Universal Encoder via the BWT

IEEE Transactions on Information Theory, 50(5), 928–937.

By: D. Baron* & Y. Bresler*

author keywords: Burrows-Wheeler transform (BWT); context tree pruning; data compression; dynamic programming; lossless source coding; minimum description length (MDL); suffix trees; tree sources; universal coding
TL;DR: An O(N) algorithm for a nonsequential semipredictive encoder whose pointwise redundancy with respect to any (unbounded depth) tree source is O(1) bits per state above Rissanen's lower bound is provided. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: April 11, 2019

2004 report

Compressing Piecewise Smooth Multidimensional Functions Using Surflets: Rate-Distortion Analysis

[Technical Report]. Electrical and Computer Engineering Department, Rice University.

By: V. Chandrasekaran, M. Wakin, D. Baron & R. Baraniuk

Source: NC State University Libraries
Added: March 24, 2019

2004 conference paper

Compression of Higher Dimensional Functions Containing Smooth Discontinuities

Proceedings of 38th Annual Conference on Information Sciences and Systems. Presented at the CISS 2004.

By: V. Chandrasekaran, M. Wakin, D. Baron & R. Baraniuk

Event: CISS 2004

Source: NC State University Libraries
Added: March 24, 2019

2004 conference paper

Probability Assignments with Worst-Case Coding Length Constraints

Proceedings of 38th Annual Conference on Information Sciences and Systems. Presented at the CISS 2004.

By: D. Baron, A. Singer & R. Baraniuk

Event: CISS 2004

Source: NC State University Libraries
Added: March 24, 2019

2004 conference paper

Redundancy Rates of Slepian-Wolf Coding

Proceedings of 42d Allerton Conference on Communication, Control, and Computing. Monticello, IL.

By: D. Baron, M. Khojastepour & R. Baraniuk

Source: NC State University Libraries
Added: March 24, 2019

2004 conference paper

Surflets: a sparse representation for multidimensional functions containing smooth discontinuities

International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings. Presented at the International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings.

By: V. Chandrasekaran*, M. Wakin*, D. Baron* & R. Baraniuk*

Event: International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings.

TL;DR: This work considers the N-dimensional Horizon class-N-dimensional functions containing a C/sup K/ smooth (N-1)-dimensional singularity separating two constant regions and derives the optimal rate-distortion function for this class and introduces the multiscale surflet representation for sparse piecewise approximation of these functions. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 23, 2019

2003 conference paper

Two-Part Codes with Low Worst-Case Redundancies for Distributed Compression of Bernoulli Sequences

Proceedings of 37th Annual Conference on Information Sciences and Systems. Presented at the CISS 2003.

By: D. Baron, Y. Bresler & M. Mihcak

Event: CISS 2003

Source: NC State University Libraries
Added: March 24, 2019

2002 journal article

Coding schemes for multislot messages in multichannel ALOHA with deadlines

IEEE Transactions on Wireless Communications, 1(2), 292–301.

By: D. Baron* & Y. Birk

author keywords: coding; deadline; delay; energy-efficient design; multichannel ALOHA; reservation ALOHA; satellite
TL;DR: This paper proposes schemes for increasing the capacity (maximum attainable throughput) of multichannel slotted ALOHA subject to meeting a user-specified deadline with a (high) required probability, thereby jointly capturing the users' requirements and the system owner's desires. (via Semantic Scholar)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy (OpenAlex)
Sources: Crossref, NC State University Libraries
Added: March 20, 2019

2002 journal article

Multiple Working Points in Multichannel ALOHA with Deadlines

Wireless Networks, 8(1), 5–11.

By: D. Baron & Y. Birk

Source: NC State University Libraries
Added: March 23, 2019

2001 report

Linear Complexity MDL Universal Coding with the BWT

(Technical Report No. UILU-ENG-01-2213). Coordinated Science Laboratory, University of Illinois.

By: D. Baron & Y. Bresler

Source: NC State University Libraries
Added: March 24, 2019

2001 conference paper

Linear Complexity MDL Universal Coding with the BWT

Baron, D., & Bresler, Y. (2001, June). Presented at the Recent Results Session, IEEE International Symposium on Information Theory (ISIT2001).

By: D. Baron & Y. Bresler

Event: Recent Results Session, IEEE International Symposium on Information Theory (ISIT2001)

Source: NC State University Libraries
Added: March 25, 2019

2001 report

Multiround Coding and Coding-Reservation for Multislot Messages in Multichannel ALOHA with Deadlines

(Technical Report No. EE Pub 1293). Electrical Engineering Department, Technion.

By: D. Baron & Y. Birk

Source: NC State University Libraries
Added: March 24, 2019

2001 journal article

On the cost of worst case coding length constraints

IEEE Transactions on Information Theory, 47(7), 3088–3090.

By: D. Baron* & A. Singer*

author keywords: data compression; Fibonacci numbers; Huffman coding; redundancy; source coding; uniquely decodable
TL;DR: This work investigates the redundancy that arises from adding a worst case length constraint to uniquely decodable fixed-to-variable codes over achievable Huffman (1952) codes, and shows that the cost for adding constraints on the worst case coding length is small, and the resulting bound is related to the Fibonacci numbers. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: March 20, 2019

2000 report

Capacity Maximization in Multichannel Slotted ALOHA with Deadlines - an Overview

(Technical Report No. EE Pub 1248, CCIT Report 314). Electrical Engineering Department, Technion.

By: Y. Birk & D. Baron

Source: NC State University Libraries
Added: March 25, 2019

2000 report

Coding Schemes for Multislot Messages in Multichannel ALOHA with Deadlines

(Technical Report No. EE Pub 1241, CIT Report 307). Electrical Engineering Department, Technion.

By: D. Baron & Y. Birk

Source: NC State University Libraries
Added: March 25, 2019

2000 report

Multiple Working Points in Multichannel ALOHA with Deadlines

(Technical Report No. EE Pub 1240, CCIT Report 306). Electrical Engineering Department, Technion.

By: D. Baron & Y. Birk

Source: NC State University Libraries
Added: March 25, 2019

2000 report

On the Merits of Impure Multi-Copy Schemes for MultiChannel Slotted ALOHA with Deadlines

(Technical Report No. EE Pub 1249, CCIT Report 315). Electrical Engineering Department, Technion.

By: D. Baron & Y. Birk

Source: NC State University Libraries
Added: March 25, 2019

2000 conference paper

Tree Source Identification with the Burrows Wheeler Transform

Proceedings of 34th Annual Conference on Information Sciences and Systems, 2, FA1–10 - FS1–15. Princeton, NJ.

By: D. Baron & Y. Bresler

Event: CISS2000

Source: NC State University Libraries
Added: March 24, 2019

1999 conference paper

On the use of Multiple Working Points in Multichannel ALOHA with Deadlines

Proceedings of 37th Allerton Conference on Communication, Control, and Computing, 728–737. Monticello, IL.

By: D. Baron & Y. Birk

Source: NC State University Libraries
Added: March 24, 2019

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