Disjoint uniquely decodable codebooks for noiseless synChronized multiple-access adder channels are studied. Codebooks are applicable to multiple-access systems in which the number of transmitting users varies over th...
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Disjoint uniquely decodable codebooks for noiseless synChronized multiple-access adder channels are studied. Codebooks are applicable to multiple-access systems in which the number of transmitting users varies over the life of the system. Several designs of codebooks, based on certain integer sets from {0, 1, 2, 3, ..., 2n - 1), are presented. They are restricted to codebooks which have the rate sum above one and simple and efficient decoding algorithms.
The word error probability of linear block codes is computed for diversity systems with maximal ratio combining in mobile communications with three decoding algorithms: error correction (EC), error/erasure correction ...
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The word error probability of linear block codes is computed for diversity systems with maximal ratio combining in mobile communications with three decoding algorithms: error correction (EC), error/erasure correction (EEC), and maximum likelihood (ML) soft decoding algorithm. Ideal interleaving is assumed. EEC gives 0.1-1.5 dB gain over EC. The gain of EEC over EC decreases as the number of diversity channels increases. ML soft gives 1.8-5.5 dB gain over EC.
Sequences of events in noise-driven excitable systems with slow variables often show serial correlations among their intervals of events. Here, we employ a master equation for generalized non-renewal processes to calc...
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Sequences of events in noise-driven excitable systems with slow variables often show serial correlations among their intervals of events. Here, we employ a master equation for generalized non-renewal processes to calculate the interval and count statistics of superimposed processes governed by a slow adaptation variable. For an ensemble of neurons with spike-frequency adaptation, this results in the regularization of the population activity and an enhanced postsynaptic signal decoding. We confirm our theoretical results in a population of cortical neurons recorded in vivo.
A hybrid coding scheme using repeat-accumulate (RA) code and polar code as subcodes is presented to improve the performance of block error probability. As the simplest turbo-like code, punctured RA code is introduced ...
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A hybrid coding scheme using repeat-accumulate (RA) code and polar code as subcodes is presented to improve the performance of block error probability. As the simplest turbo-like code, punctured RA code is introduced to improve the reliability of the hybrid scheme. A low complexity algorithm, belief propagation/successive cancellation hybrid decoding algorithm is proposed. Compared with polar code, this hybrid scheme can provide 0.3 dB coding gain with the code length 1024 and code rate 1/2. In contrast with RA code, it has no error floor in the additive white Gaussian noise channel.
A polar coding method to construct a distributed source coding scheme which can achieve any point on the dominant face of the Slepian-Wolf rate region for sources with uniform marginals is proposed. Source encoding an...
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A polar coding method to construct a distributed source coding scheme which can achieve any point on the dominant face of the Slepian-Wolf rate region for sources with uniform marginals is proposed. Source encoding and decoding operations are performed using efficient algorithms which makes practical implementation feasible. Simulation results are given to exhibit the performance of the presented method.
Classes of systematic codes correcting burst asymmetric or unidirectional errors are proposed. These codes have less check bits than ordinary burst error correcting codes. decoding algorithms for the proposed codes ar...
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Classes of systematic codes correcting burst asymmetric or unidirectional errors are proposed. These codes have less check bits than ordinary burst error correcting codes. decoding algorithms for the proposed codes are also presented. Encoding and decoding of the codes is very easy.
Soft errors that affect flip-flops are a major issue in advanced electronic circuits. As technology scales, multiple bit errors become more likely. This limits the applicability of traditional protection techniques li...
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Soft errors that affect flip-flops are a major issue in advanced electronic circuits. As technology scales, multiple bit errors become more likely. This limits the applicability of traditional protection techniques like triplication with voting or single error correction codes that can correct only one error. Multiple errors tend to affect adjacent bits, and therefore it is interesting to use error correction codes that can correct adjacent errors. The issue with these codes is that they require a large area and delay that limits their use to protect flip-flops in circuits. Presented are codes that can be implemented with low area and delay and can correct multiple adjacent errors.
Brain decoding algorithms form an important part of the arsenal of analysis tools available to neuroscientists, allowing for a more detailed study of the kind of information represented in patterns of cortical activit...
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Brain decoding algorithms form an important part of the arsenal of analysis tools available to neuroscientists, allowing for a more detailed study of the kind of information represented in patterns of cortical activity. While most current decoding algorithms focus on estimating a single, most likely stimulus from the pattern of noisy fMRI responses, the presence of noise causes this estimate to be uncertain. This uncertainty in stimulus estimates is a potentially highly relevant aspect of cortical stimulus processing, and features prominently in Bayesian or probabilistic models of neural coding. Here, we focus on sensory uncertainty and how best to extract this information with fMRI. We first demonstrate in simulations that decoding algorithms that take into account correlated noise between fMRI voxels better recover the amount of uncertainty (quantified as the width of a probability distribution over possible stimuli) associated with the decoded estimate. Furthermore, we show that not all correlated variability should be treated equally, as modeling tuning-dependent correlations has the greatest impact on decoding performance. Next, we examine actual noise correlations in human visual cortex, and find that shared variability in areas V1-V3 depends on the tuning properties of fMRI voxels. In line with our simulations, accounting for this shared noise between similarly tuned voxels produces important benefits in decoding. Our findings underscore the importance of accurate noise models in fMRI decoding approaches, and suggest a statistically feasible method to incorporate the most relevant forms of shared noise.
There have been numerous applications developed for decoding and visualization of ab1 DNA sequencing files for Windows and MAC platforms, yet none exists for the increasingly popular smartphone operating systems. The ...
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There have been numerous applications developed for decoding and visualization of ab1 DNA sequencing files for Windows and MAC platforms, yet none exists for the increasingly popular smartphone operating systems. The ability to decode sequencing files cannot easily be carried out using browser accessed Web tools. To overcome this hurdle, we have developed a new native app called DNAApp that can decode and display ab1 sequencing file on Android and iOS. In addition to in-built analysis tools such as reverse complementation, protein translation and searching for specific sequences, we have incorporated convenient functions that would facilitate the harnessing of online Web tools for a full range of analysis. Given the high usage of Android/iOS tablets and smartphones, such bioinformatics apps would raise productivity and facilitate the high demand for analyzing sequencing data in biomedical research.
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