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4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE)

作者： Matthews, Brett Kim, Jonathan Brumberg, Jonathan S. Clements, Mark Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA Boston Univ Dept Cognit & Neural Syst Boston MA 02215 USA

ISBN: (纸本)9781424447138

Neural prosthetic systems for motor control and communication have produced striking results in recent studies with non-human primates and human volunteers. We describe a new approach in our ongoing work toward developing an intracortical neural prosthesis for speech restoration with a 26 year old human volunteer with tetraplegia (including loss of vocal and facial muscle control). We propose to use hidden Markov models (HMMs) to decode neural firing activity in speech motor cortex. We show how classical and recent approaches to automatic speech recognition (ASR) apply directly to the decoding stage of a neural prosthesis. We outline a series of experiments in collecting cortical neural firing data from our human volunteer, and discuss important challenges and considerations in implementing an HMM framework for a neural speech prosthesis.

关键词： Neural Prostheses Human Volunteers Speech probabilistic decoding Facial Muscles Quadriplegia Primary Motor Cortex decoding

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Sparse Output Coding for Scalable Visual Recognition

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INTERNATIONAL JOURNAL OF COMPUTER VISION 2016年第1期119卷 60-75页

作者： Zhao, Bin Xing, Eric P. Carnegie Mellon Univ Sch Comp Sci Pittsburgh PA 15213 USA

Many vision tasks require a multi-class classifier to discriminate multiple categories, on the order of hundreds or thousands. In this paper, we propose sparse output coding, a principled way for large-scale multi-class classification, by turning high-cardinality multi-class categorization into a bit-by-bit decoding problem. Specifically, sparse output coding is composed of two steps: efficient coding matrix learning with scalability to thousands of classes, and probabilistic decoding. Empirical results on object recognition and scene classification demonstrate the effectiveness of our proposed approach.

关键词： Scalable classification Output coding probabilistic decoding Object recognition Scene recognition

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On the Relationship Between Belief Propagation decoding and Joint Maximum Likelihood Detection

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IEEE TRANSACTIONS ON COMMUNICATIONS 2010年第10期58卷 2753-2758页

作者： Walsh, John MacLaren Regalia, Phillip Allan Drexel Univ Philadelphia PA 19104 USA Catholic Univ Amer Washington DC 20064 USA

Belief propagation, via a novel reinterpretation of the Bethe free energy's pseudo-dual, is shown to be related to a novel relaxation of maximum likelihood detection via a constrained optimization. The conventional maximum likelihood detection falls out for a zero constraint, and belief propagation's fixed points are obtained for other constraint values.

关键词： Belief propagation factor graphs probabilistic decoding turbo decoding iterative decoding

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Bounded distance plus 1 soft-decision Reed-Solomon decoding

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IEEE TRANSACTIONS ON INFORMATION THEORY 1996年第3期42卷 704-720页

作者： Berlekamp, E Hazelnut Berkeley CA USA

We present a new Reed-Solomon decoding algorithm, which embodies several refinements of an earlier algorithm. Some portions of this new decoding algorithm operate on symbols of length Igq bits;other portions operate on somewhat longer symbols. In the worst case, the total number of calculations required by the new decoding algorithm is proportional to nr, where n is the code's block length and r is its redundancy. This worst case workload is very similar to prior algorithms. But in many applications, average-case workload and error-correcting performance are both much better. The input to the new algorithm consists of n received symbols from GF(q), and rr nonnegative real numbers, each of which is the reliability of the corresponding received symbol. Any conceivable errata pattern has a ''score'' equal to the sum of the reliabilities of its locations with nonzero errata values. A max-likelihood decoder would find the minimum score over all possible errata patterns. Our new decoding algorithm finds the minimum score only over a subset of these possible errata patterns. The errata within any candidate errata pattern may be partitioned into ''errors'' and ''erasures,'' depending on whether the corresponding reliabilities are above or below an ''erasure threshold.'' Different candidate errata patterns may have different thresholds, each chosen to minimize its corresponding ERRATA COUNT, which is defined as 2 . (number of errors) c (number of erasures). The new algorithm finds an errata pattern with minimum score among all errata patterns for which ERRATA COUNT less than or equal to r + 1 where r is the redundancy of the RS code. This is one check symbol better than conventional RS decoding algorithms. Conventional algorithms also require that the erasure threshold be set a priori;the new algorithm obtains the best answer over all possible settings of the erasure threshold. Conventional cyclic RS codes have length n = q - 1, and their locations correspond to the nonzero

关键词： decoding algorithms Reed-Solomon codes soft decisions doubly extended codes algebraic decoding decoding beyond half minimum distance probabilistic decoding best case decoding queued decoding Generalized Minimum Distance decoding bounded distance decoding

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Sparse-graph codes for quantum error correction

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IEEE TRANSACTIONS ON INFORMATION THEORY 2004年第10期50卷 2315-2330页

作者： MacKay, DJC Mitchison, G McFadden, PL Cavevdish Lab Dept Phys Cambridge CB3 0HE England MRC Mol Biol Lab Cambridge CB2 2QH England Dept Appl Math & Theoret Phys Cambridge CB3 0WA England

Sparse-graph codes appropriate for use in quantum error-correction are presented. Quantum error-correcting codes based on sparse graphs are of interest for three reasons. First, the best codes currently known for classical channels are based on sparse graphs. Second, sparse-graph codes keep the number of quantum interactions associated with the quantum error-correction process small: a constant number per quantum bit, independent of the block length. Third, sparse-graph codes often offer great flexibility with respect to block length and rate. We believe some of the codes we present are unsurpassed by previously published quantum error-correcting codes.

关键词： error-correction codes probabilistic decoding quantum error correction

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Reliability-based soft-decision decoding with iterative information set reduction

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IEEE TRANSACTIONS ON INFORMATION THEORY 2002年第12期48卷 3101-3106页

作者： Fossorier, MPC Univ Hawaii Dept Elect Engn Honolulu HI 96822 USA

In this correspondence, the reliability-based decoding approach using the reprocessing of the most reliable information set only is extended into the iterative reprocessing of several information sets. At the end of each information set reprocessing, some information bits are delivered by the decoder. Consequently, information sets with decreasing cardinality values are considered at each iteration. A tight upper bound on the error performance achieved by this new method is derived. Compared to previously proposed competitive approaches, this new method reduces the number of candidate codewords needed to achieve practically optimum decoding. Importantly, it also preserves the very simple structured implementation of the order statistic decoding.

关键词： block codes information set decoding maximum-likelihood decoding (MLD) order statistic decoding probabilistic decoding soft-decision decoding

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Reliability-based soft-decision decoding with multiple biases

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IEEE TRANSACTIONS ON INFORMATION THEORY 2007年第1期53卷 105-120页

作者： Jin, Wenyi Fossorier, Marc P. C. Univ Hawaii Manoa Dept Elect Engn Honolulu HI 96822 USA

In this paper, a new reliability-based soft-decision decoding algorithm is presented. This algorithm repeatedly uses biased reliability values to construct the most-reliable-basis (MRB). As a result, this new method makes use of multiple information sets in a stochastic way. Compared to previously proposed competitive approaches, this new method produces a more efficient MRB reprocessing type algorithm to achieve near maximum-likelihood decoding (MLD) performance with a proper choice of the bias value. It can be combined with any MRB reprocessing type algorithm and in each case, a tight performance analysis can be derived.

关键词： linear block codes list decoding maximum-likelihood decoding order statistics probabilistic decoding Reed-Solomon codes

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Near Shannon limit performance of low density parity check codes

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ELECTRONICS LETTERS 1997年第6期33卷 457-458页

作者： MacKay, DJC Neal, RM UNIV TORONTO DEPT STAT TORONTO ON M5S 1A4 CANADA UNIV TORONTO DEPT COMP SCI TORONTO ON M5S 1A4 CANADA

The authors report the empirical performance of Gallager's low density parity check codes on Gaussian channels. They show that performance substantially better than that of standard convolutional and concatenated ... 详细信息

关键词： probabilistic decoding error correction codes

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Low Density Parity Check codes over GF(q)

Low Density Parity Check codes over GF(q)

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IEEE Information Theory Workshop

作者： Davey, MC MacKay, DJC Univ Cambridge Cavendish Lab Cambridge CB3 0HE England

ISBN: (纸本)0780344081

Binary Low Density Parity Check (LDPC) codes have been shown to have near Shannon limit performance when decoded using a probabilistic decoding algorithm. The analogous codes defined over finite fields GF(q) of order q > 2 show significantly improved performance. We present the results of Monte Carlo simulations of the decoding of infinite LDPC Codes which can be used to obtain good constructions for finite Codes. We also present empirical results for the Gaussian channel including a rate 1/4 code with bit error probability of 10(-4) at E-b/N-o = -0.05dB.

关键词： low density parity check codes Monte Carlo technique Gaussian channels Parity check bit error probability Codes decoding valid parity check character parity check probabilistic decoding Shannon limit

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A comparison between "Most-reliable-basis reprocessing" strategies

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2002年第7期E85A卷 1727-1741页

作者： Valembois, A Fossorier, M Univ Hawaii Manoa Honolulu HI 96822 USA

In this semi-tutorial paper, the reliability-based decoding approaches using the reprocessing of the most reliable information set are investigated. This paper somehow homogenizes and compares former different studies, hopefully improving the overall transparency, and completing each one with tricks provided by the others. A couple of sensible improvements are also suggested. However, the main goal remains to integrate and compare recent works based on a similar general approach, which have unfortunately been performed in parallel without much efforts of comparison up to now. Their respective (dis) advantages, especially in terms of average or maximum complexity are elaborated. We focus on suboptimum decoding while some works to which we refer were developed for maximum likelihood decoding (MILD). No quantitative error performance analysis is provided, although we are in a position to benefit from some qualitative considerations;and to compare different strategies in terms of higher or lower expected error performances for a same complexity. With simulations, however, it turns out that all considered approaches perform very closely to each other, which was not especially obvious at first sight. The simplest strategy proves also the fastest in terms of CPU-time, but we indicate ways to implement the other ones so that they get very close to each other from this point of view also. On top of relying on the same intuitive principle;the studied algorithms are thus also unified from the point of view of their error performances and computational cost.

关键词： soft decision decoding probabilistic decoding maximum likelihood decoding block codes

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