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IEEE JOURNAL ON SELECTED AREAS IN INFORMATION THEORY 2024年 5卷 509-519页

作者： Feldman, Ariel K. Venkatesh, Praveen Weber, Douglas J. Grover, Pulkit Carnegie Mellon Univ Neurosci Inst Pittsburgh PA 15213 USA Allen Inst Seattle WA 98109 USA Univ Washington Dept Physiol & Biophys Seattle WA 98109 USA Carnegie Mellon Univ Mech Engn Dept & Neurosci Inst Pittsburgh PA 15213 USA Carnegie Mellon Univ Elect & Comp Engn Dept & Neurosci Inst Pittsburgh PA 15213 USA

This paper brings together topics of two of Berger's main contributions to information theory: distributed source coding, and living information theory. Our goal is to understand which information theory techniques can be helpful in understanding a distributed source coding strategy used by the natural world. Towards this goal, we study the example of the encoding of location of an animal by grid cells in its brain. We use information measures of partial information decomposition (PID) to assess the unique, redundant, and synergistic information carried by multiple grid cells, first for simulated grid cells utilizing known encodings, and subsequently for data from real grid cells. In all cases, we make simplifying assumptions so we can assess the consistency of specific PID definitions with intuition. Our results suggest that the measure of PID proposed by Bertschinger et al. (Entropy, 2014) provides intuitive insights on distributed source coding by grid cells, and can be used for subsequent studies for understanding grid-cell encoding as well as broadly in neuroscience.

关键词： distributed source coding grid cells neuroscience partial information decomposition

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A distributed source coding technique for correlated images using turbo-codes

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IEEE COMMUNICATIONS LETTERS 2002年第9期6卷 379-381页

作者： Liveris, AD Xiong, ZX Georghiades, CN Texas A&M Univ Dept Elect Engn College Stn TX 77843 USA

The Slepian-Wolf theorem states that the output of two correlated sources can be compressed to the same extent without loss, whether they communicate with each other or not, provided that decompression takes place at a joint decoder. We present a distributed source coding scheme for correlated images which uses modulo encoding of pixel values and encoding (compression) of the resulting symbols with binary and nonbinary turbo-codes, so that larger rate savings than using modulo encoding alone are achieved, practically without loss.

关键词： concatenated codes distributed source coding interleaved codes Turbo codes

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Near lossless compression of hyperspectral images based on distributed source coding

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Science China(Information Sciences) 2012年第11期55卷 2646-2655页

作者： NIAN YongJian1,WAN JianWei1,TANG Yi1 & CHEN Bo2 1College of Electronic Science and Engineering,National University of Defense Technology,Changsha,410073,China 2College of Science,National University of Defense Technology,Changsha,410073,China 1. College of Electronic Science and Engineering National University of Defense Technology Changsha 410073 China 2. College of Science National University of Defense Technology Changsha 410073 China

Effective compression technique of on-board hyperspectral images has been an active topic in the field of hyperspectral remote *** order to solve the effective compression of on-board hyperspectral images,a new distributed near lossless compression algorithm based on multilevel coset codes is *** to the diverse importance of each band,a new adaptive rate allocation algorithm is proposed,which allocates rational rate for each band according to the size of weight factor defined for hyperspectral images subject to the target rate *** prediction is introduced for Slepian-Wolf lossless coding and an optimal quantization algorithm is presented under the correct reconstruction of Slepian-Wolf decoder,which minimizes the distortion of reconstructed hyperspectral images under the target *** Slepian-Wolf encoder exploits the correlation of the quantized values to generate the final bit *** results show that the proposed algorithm has both higher compression efficiency and lower encoder complexity than several existing classical algorithms.

关键词： hyperspectral images near lossless compression Slepian-Wolf coding distributed source coding

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Federated Learning With Lossy distributed source coding: Analysis and Optimization

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IEEE TRANSACTIONS ON COMMUNICATIONS 2023年第8期71卷 4561-4576页

作者： Yang, Huiyuan Ding, Tian Yuan, Xiaojun Univ Elect Sci & Technol China Natl Key Lab Wireless Commun Chengdu 611731 Peoples R China Chinese Univ Hong Kong Dept Informat Engn Hong Kong Peoples R China

Recently, federated learning (FL), which replaces data sharing with model sharing, has emerged as an efficient and privacy-friendly machine learning (ML) paradigm. One of the main challenges in FL is the huge communication cost for model aggregation. Many compression/quantization schemes have been proposed to reduce the communication cost for model aggregation. However, the following question remains unanswered: What is the fundamental trade-off between the communication cost and the FL convergence performance? In this paper, we manage to answer this question. Specifically, we first put forth a general framework for model aggregation performance analysis based on the rate-distortion theory. Under the proposed analysis framework, we derive an inner bound of the rate-distortion region of model aggregation. We then conduct an FL convergence analysis to connect the aggregation distortion and the FL convergence performance. We formulate an aggregation distortion minimization problem to improve the FL convergence performance. Two algorithms are developed to solve the above problem. Numerical results on aggregation distortion, convergence performance, and communication cost demonstrate that the baseline model aggregation schemes still have great potential for further improvement.

关键词： Federated learning model aggregation rate-distortion theory distributed source coding Berger-Tung coding majorization-minimization

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source-Optimized Clustering for distributed source coding

Source-Optimized Clustering for Distributed Source Coding

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IEEE Global Telecommunications Conference (GLOBECOM 06)

作者： Maierbacher, Gerhard Barros, Joao Univ Porto Dept Comp Sci Oporto Portugal

ISBN: (纸本)9781424403561

Motivated by the design of low-complexity distributed quantizers and iterative decoding algorithms that leverage the correlation in the data picked up by a large-scale sensor network, we address the problem of finding correlation preserving clusters. To construct a factor graph describing the statistical dependencies between sensor measurements, we develop a hierarchical clustering algorithm that minimizes the Kullback Leibler Distance between known and approximated source statistics. Finally, we show how the clustering result can be exploited in the design of index assignments for distributed quantization and source-channel decoders of manageable complexity.

关键词： sensor networks distributed source coding clustering trees quantization Kullback-Leibler distance

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SIDE-INFORMATION-ADAPTIVE distributed source coding

SIDE-INFORMATION-ADAPTIVE DISTRIBUTED SOURCE CODING

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IEEE International Conference on Image Processing

作者： Varodayan, David Girod, Bernd Stanford Univ Informat Syst Lab Stanford CA 94305 USA

ISBN: (纸本)9781424479948

Consider distributed source coding in which each block of the source at the encoder is associated with multiple candidates for side information at the decoder, just one of which is statistically dependent on the source block. Our encoder codes the source as syndrome bits and also sends a portion of it uncoded as doping bits. The decoder adaptively discovers the best side information candidates for each block of the source. The main contribution is a method based on density evolution to analyze and design the coding performance. Experimental results show that the density evolution technique is accurate in modeling the codec and optimizing its doping rate.

关键词： distributed source coding sum-product algorithm density evolution

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Rate Adaptive distributed source coding for Wireless Applications 49

Rate Adaptive Distributed Source Coding for Wireless Applica...

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2015 49th Asilomar Conference on Signals, Systems and Computers

作者： Chang, Nicholas B. Liberti, Joseph C. Gross, Mike Appl Commun Sci 331 Newman Springs Rd Red Bank NJ 07701 USA Lab Telecommun Sci College Pk MD 20740 USA

ISBN: (纸本)9781467385763

distributed source coding techniques enable distributed receivers to independently compress samples to a rate above the Slepian-Wolf bound, by leveraging statistical correlations between different receivers observations. The wireless channel can impose many compression challenges, such as unknown or dynamic compression bounds due to time-varying fading and mobility. This work derives a novel rate adaptive non-binary distributed source coding scheme which is motivated by these challenges. Applications are derived for distributed detection and distributed multiple-input multiple-output (MIMO) reception. Results demonstrate strong performance with these applications along with near-bound compression at various SNR levels and channel realizations.

关键词： distributed source coding distributed detection distributed MIMO Slepian-Wolf capacity

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Interplay between routing and distributed source coding in Wireless Sensor Network

Interplay between routing and distributed source coding in W...

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IEEE International Conference on Communications (ICC 2007)

作者： Wang, Honggang Peng, Dongming Wang, Wei Sharif, Hamid Chen, Hsiao-Hwa Univ Nebraska Lincoln Dept Comp & Elect Engn Omaha NE USA Natl Sun Yat Sen Univ Inst Commun Engn Kaohsiung 80424 Taiwan

ISBN: (纸本)9781424403523

Recent Advances in distributed source coding (DSC) for mission-driven Wireless Sensor Networks (WSN) are related to the coding for multiple correlated sensors in applications such as real time target tracking and environment monitoring. The characteristic of these DSC applications provides significant potential opportunities in the associated sensor network to utilize multirate transmissions for enhancing network performance. In this paper, we study a methodology for interplay optimization between routing and DSC in WSN, and propose a novel multirate based routing scheme for mission-driven DSC applications that considerably extends network lifetime. The proposed scheme adopts the rate assignment based on the residual energy, and employs a joint rate and energy scheduling mechanism to meet the end-to-end transmission rate constraint, information precision requirement, and the energy constraints in the network for DSC. Simulation results show that this multirate based routing scheme achieves significantly longer network lifetime compared to other existing research in WSN for DSC applications.

关键词： distributed source coding network lifetime multirate Wireless Sensor Network

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LOCALIZATION OF TAMPERING IN CONTRAST AND BRIGHTNESS ADJUSTED IMAGES USING distributed source coding AND EXPECTATION MAXIMIZATION

LOCALIZATION OF TAMPERING IN CONTRAST AND BRIGHTNESS ADJUSTE...

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15th IEEE International Conference on Image Processing (ICIP 2008)

作者： Lin, Yao-Chung Varodayan, David Fink, Torsten Bellers, Erwin Girod, Bernd Stanford Univ Informat Syst Lab Stanford CA 94305 USA TriMedia Ctr Excellence NXP Semiconductors San Jose CA 95131 USA

ISBN: (纸本)9781424417650

Media authentication and tampering localization are important in content delivery via untrusted intermediaries, such as peer-to-peer (P2P) file sharing. Many differently encoded versions of a media file might exist. Our previous work applied distributed source coding to authenticate the legitimate diversity of encoded images and also localize the tampered regions in an inauthentic image. The authentication/localization decoder was supplied with a Slepian-Wolf encoded image projection as authentication data. We extend our scheme to localize tampering in contrast and brightness adjusted images using an Expectation Maximization algorithm at the decoder. Experimental results demonstrate that tampered image blocks can be identified with high probability using data of only a few hundred bytes for a 512x512 image.

关键词： Image authentication tampering localization distributed source coding Expectation Maximization

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Taming underlying design for energy efficient distributed source coding in multirate wireless sensor network

Taming underlying design for energy efficient distributed so...

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65th IEEE Vehicular Technology Conference

作者： Wang, Wei Peng, Dongming Wang, Honggang Sharif, Hamid Chen, Hsiao-Hwa Univ Nebraska Lincoln NE 68583 USA Natl Sun Yat Sen Univ Kaohsiung 80424 Taiwan

ISBN: (纸本)9781424402656

Signal processing applications such as distributed source coding (DSC) in Wireless Sensor Network (WSN) are often multirate in nature, which provide additional significant opportunities in WSN design for achieving energy efficiency. In this paper, we analyze the DSC traffic for signal processing applications in multirate WSN and propose a novel rate oriented approach with MAC and PRY cross layer utilization to achieve high energy efficiency. Simulation results show that the proposed approach achieves significant energy efficiency by a factor of three while maintaining the transmission quality in WSN. This approach can be easily extended to other WSN MAC and PRY designs, providing multirate service to application layer to allow achieving higher energy efficiency.

关键词： energy efficiency multirate signal processing wireless sensor network distributed source coding

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