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A Generalized BlahutArimoto Algorithm
, 2002
"... Kavcic proposed in [1] an algorithm that optimizes the parameters of a Markov source at the input to a finitestate machine channel in order to maximize the mutual information rate. Numerical results for several channels indicated that his algorithm gives capacityachieving input distributions. In t ..."
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Cited by 8 (1 self)
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Kavcic proposed in [1] an algorithm that optimizes the parameters of a Markov source at the input to a finitestate machine channel in order to maximize the mutual information rate. Numerical results for several channels indicated that his algorithm gives capacityachieving input distributions
Extension of the Blahut–Arimoto Algorithm for Maximizing Directed Information
"... Abstract—In this paper, we extend the Blahut–Arimoto algorithm for maximizing Massey’s directed information. The algorithm can be used for estimating the capacity of channels with delayed feedback, where the feedback is a deterministic function of the output. In order to maximize the directed inform ..."
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Cited by 8 (5 self)
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Abstract—In this paper, we extend the Blahut–Arimoto algorithm for maximizing Massey’s directed information. The algorithm can be used for estimating the capacity of channels with delayed feedback, where the feedback is a deterministic function of the output. In order to maximize the directed
A generalization of the BlahutArimoto algorithm to finitestate channels
 IEEE Trans. Inf. Theory
, 2008
"... Abstract—The classical Blahut–Arimoto algorithm (BAA) is a wellknown algorithm that optimizes a discrete memoryless source (DMS) at the input of a discrete memoryless channel (DMC) in order to maximize the mutual information between channel input and output. This paper considers the problem of opti ..."
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Cited by 23 (5 self)
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Abstract—The classical Blahut–Arimoto algorithm (BAA) is a wellknown algorithm that optimizes a discrete memoryless source (DMS) at the input of a discrete memoryless channel (DMC) in order to maximize the mutual information between channel input and output. This paper considers the problem
BlahutArimoto Algorithms for Computing Channel Capacity and RateDistortion
 With Side Information,” IEEE International Symposium on Information Theory (ISIT
"... Abstract — This paper presents numerical algorithms for the computation of the capacity for channels with noncausal transmitter side information (the Gel’fandPinsker problem) and the ratedistortion function for source coding with decoder side information (the WynerZiv problem). The algorithms ar ..."
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Cited by 25 (0 self)
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Abstract — This paper presents numerical algorithms for the computation of the capacity for channels with noncausal transmitter side information (the Gel’fandPinsker problem) and the ratedistortion function for source coding with decoder side information (the WynerZiv problem). The algorithms
BlahutArimoto Algorithm and Code Design for ActionDependent Source Coding Problems
"... Abstract—The source coding problem with actiondependent side information at the decoder has recently been introduced to model data acquisition in resourceconstrained systems. In this paper, an efficient BlahutArimototype algorithm for the numerical computation of the ratedistortioncost functio ..."
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Abstract—The source coding problem with actiondependent side information at the decoder has recently been introduced to model data acquisition in resourceconstrained systems. In this paper, an efficient BlahutArimototype algorithm for the numerical computation of the rate
1BlahutArimoto Algorithm and Code Design for ActionDependent Source Coding Problems
, 2013
"... The source coding problem with actiondependent side information at the decoder has recently been introduced to model data acquisition in resourceconstrained systems. In this paper, an efficient algorithm for numerical computation of the ratedistortioncost function for this problem is proposed, a ..."
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on LDGM codes and message passing. Through numerical examples, the proposed code design is shown to achieve performance close to the lower bound dictated by the ratedistortioncost function. Index Terms Ratedistortion theory, side information “vending machine”, BlahutArimoto algorithm, code design
Information Geometric Formulation and Interpretation of Accelerated BlahutArimototype Algorithms
 IEEE International Workshop on Information Theory, 24–29 Oct
, 2004
"... Abstract — We propose two related classes of iterative algorithms for computing the capacity of discrete memoryless channels. The celebrated BlahutArimoto algorithm is a special case of our framework. The formulation of these algorithms is based on the natural gradient and proximal point methods. W ..."
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Cited by 14 (0 self)
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Abstract — We propose two related classes of iterative algorithms for computing the capacity of discrete memoryless channels. The celebrated BlahutArimoto algorithm is a special case of our framework. The formulation of these algorithms is based on the natural gradient and proximal point methods
The information bottleneck method
 University of Illinois
, 1999
"... We define the relevant information in a signal x ∈ X as being the information that this signal provides about another signal y ∈ Y. Examples include the information that face images provide about the names of the people portrayed, or the information that speech sounds provide about the words spoken. ..."
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Cited by 545 (38 self)
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consistent equations for the coding rules X → ˜ X and ˜ X → Y. Solutions to these equations can be found by a convergent re–estimation method that generalizes the Blahut–Arimoto algorithm. Our variational principle provides a surprisingly rich framework for discussing a variety of problems in signal
DOI: 10.1109/ICASSP.2009.4960131 GEOMETRICAL INTERPRETATION AND IMPROVEMENTS OF THE
, 2010
"... The paper first recalls the Blahut Arimoto algorithm for computing the capacity of arbitrary discrete memoryless channels, as an example of an iterative algorithm working with probability density estimates. Then, a geometrical interpretation of this algorithm based on projections onto linear and exp ..."
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The paper first recalls the Blahut Arimoto algorithm for computing the capacity of arbitrary discrete memoryless channels, as an example of an iterative algorithm working with probability density estimates. Then, a geometrical interpretation of this algorithm based on projections onto linear
1 Squeezing the ArimotoBlahut Algorithm for Faster Convergence
"... Abstract—The Arimoto–Blahut algorithm for computing the capacity of a discrete memoryless channel is revisited. A socalled “squeezing ” strategy is used to design algorithms that preserve its simplicity and monotonic convergence properties, but have provably better rates of convergence. Index Terms ..."
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Abstract—The Arimoto–Blahut algorithm for computing the capacity of a discrete memoryless channel is revisited. A socalled “squeezing ” strategy is used to design algorithms that preserve its simplicity and monotonic convergence properties, but have provably better rates of convergence. Index
Results 1  10
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