Topic
Blahut–Arimoto algorithm
About: Blahut–Arimoto algorithm is a research topic. Over the lifetime, 26 publications have been published within this topic receiving 2466 citations.
Papers
TL;DR: A simple algorithm for computing channel capacity is suggested that consists of a mapping from the set of channel input probability vectors into itself such that the sequence of probability vectors generated by successive applications of the mapping converges to the vector that achieves the capacity of the given channel.
Abstract: By defining mutual information as a maximum over an appropriate space, channel capacities can be defined as double maxima and rate-distortion functions as double minima. This approach yields valuable new insights regarding the computation of channel capacities and rate-distortion functions. In particular, it suggests a simple algorithm for computing channel capacity that consists of a mapping from the set of channel input probability vectors into itself such that the sequence of probability vectors generated by successive applications of the mapping converges to the vector that achieves the capacity of the given channel. Analogous algorithms then are provided for computing rate-distortion functions and constrained channel capacities. The algorithms apply both to discrete and to continuous alphabet channels or sources. In addition, a formalization of the theory of channel capacity in the presence of constraints is included. Among the examples is the calculation of close upper and lower bounds to the rate-distortion function of a binary symmetric Markov source.
1,694 citations
TL;DR: A systematic and iterative method of computing the capacity of arbitrary discrete memoryless channels is presented and a few inequalities that give upper and lower bounds on the capacity are derived.
Abstract: A systematic and iterative method of computing the capacity of arbitrary discrete memoryless channels is presented. The algorithm is very simple and involves only logarithms and exponentials in addition to elementary arithmetical operations. It has also the property of monotonic convergence to the capacity. In general, the approximation error is at least inversely proportional to the number of iterations; in certain circumstances, it is exponentially decreasing. Finally, a few inequalities that give upper and lower bounds on the capacity are derived.
1,002 citations
TL;DR: The channel capacity for the alpha-stable channels is developed both for the symmetric and the skewed cases and numerical bounds for its lossy coding performance are provided.
Abstract: Alpha-stable distributions have found various applications in the literature especially in modelling impulsive noise in communications channels. Despite various schemes for receiver design under alpha-stable noise, the channel coding problem has not been addressed yet. In this letter, we develop the channel capacity for the alpha-stable channels both for the symmetric and the skewed cases and provide numerical bounds for its lossy coding performance. Blahut-Arimoto algorithm is used to calculate the capacity of alpha-stable channel and its efficiency is demonstrated.
52 citations
TL;DR: In this correspondence, iterative algorithms that numerically compute the capacity-power and rate-distortion functions for coding with two-sided state information are presented.
Abstract: In this correspondence, we present iterative algorithms that numerically compute the capacity-power and rate-distortion functions for coding with two-sided state information. Numerical examples are provided to demonstrate efficiency of our algorithms.
28 citations
TL;DR: Under the Poisson-excitation assumption, results from earlier study by Suksompong and Berger on the timing jitter in the leaky integrate-and-fire model of neurons are used to determine families of neural thresholding functions that are appropriate in certain interesting senses.
Abstract: Understanding how a biological neuron works has been a major goal in neuroscience. Under the Poisson-excitation assumption, results from earlier study by Suksompong and Berger on the timing jitter in the leaky integrate-and-fire (LIF) model of neurons are used to determine families of neural thresholding functions that are appropriate in certain interesting senses. Next, the neuron is treated as a communication channel for which information-theoretic quantities can be calculated. In particular, the optimal distribution of the Poisson excitation intensity is numerically evaluated along with the corresponding capacity using the Blahut-Arimoto algorithm. Simple formulas which approximate the optimal intensity distribution are given. Furthermore, the Jimbo-Kunisawa algorithm is used to explore energy-efficient operations for neuron. Finally, a rate-matching argument leads to a unique operating condition which turns out to agree with experimentally observed rate.
27 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2017 | 3 |
| 2015 | 1 |
| 2014 | 1 |
| 2013 | 3 |
| 2012 | 1 |
| 2011 | 2 |