Results 21 to 30 of about 796,535 (249)
Foundations and Trends® in Communications and Information Theory, 2019 Developing computationally-efficient codes that approach the Shannon-theoretic limits for communication and compression has long been one of the major goals of information and coding theory. There have been significant advances towards this goal in the last couple of decades, with the emergence of turbo codes, sparsegraph codes, and polar codes.
Ramji Venkataramanan +2 more
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Sparse Coding and Autoencoders [PDF]
2018 IEEE International Symposium on Information Theory (ISIT), 2018 In this new version of the paper with a small change in the distributional assumptions we are actually able to prove the asymptotic criticality of a neighbourhood of the ground truth dictionary for even just the standard squared loss of the ReLU autoencoder (unlike the regularized loss in the older version)
Akshay Rangamani +6 more
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Synthesis of a comprehensive population code for contextual features in the awake sensory cortex
eLife, 2021 How cortical circuits build representations of complex objects is poorly understood. Individual neurons must integrate broadly over space, yet simultaneously obtain sharp tuning to specific global stimulus features.
Evan H Lyall +5 more
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Reconfigurable rateless codes [PDF]
, 2009 We propose novel reconfigurable rateless codes, that are capable of not only varying the block length but also adaptively modify their encoding strategy by incrementally adjusting their degree distribution according to the prevalent channel conditions ...
Chen, Sheng +3 more
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Mathematics, 2022 Electrocardiogram (ECG) is a common and powerful tool for studying heart function and diagnosing several abnormal arrhythmias. In this paper, we present a novel classification model that combines the discriminative convolutional sparse coding (DCSC ...
Bing Zhang, Jizhong Liu
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Combinatorial Regression and Improved Basis Pursuit for Sparse Estimation [PDF]
, 2012 Sparse representations accurately model many real-world data sets. Some form of sparsity is conceivable in almost every practical application, from image and video processing, to spectral sensing in radar detection, to bio-computation and genomic signal ...
Khajehnejad, M. Amin
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Explicit Object Representation by Sparse Neural Codes [PDF]
, 2008 Neurons have been identified in the human medial temporal lobe (MTL) that display a strong selectivity for only a few stimuli (such as familiar individuals or landmark buildings) out of perhaps 100 presented to the test subject.
Waydo, Stephen J.
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IEEE Transactions on Information Theory, 2014 51 pages, 12 figures, submitted to IEEE Transactions on Information ...
Shenghao Yang 0001, Raymond W. Yeung
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Bayesian modelling of music : algorithmic advances and experimental studies of shift-invariant sparse coding [PDF]
, 2005 PhDIn order to perform many signal processing tasks such as classification, pattern recognition and coding, it is helpful to specify a signal model in terms of meaningful signal structures.
Blumensath, Thomas
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Design of LDPC Codes: A Survey and New Results [PDF]
, 2006 This survey paper provides fundamentals in the design of LDPC codes. To provide a target for the code designer, we first summarize the EXIT chart technique for determining (near-)optimal degree distributions for LDPC code ensembles.
Ryan, William E. +11 more
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