Algebraic information theory and stochastic resonance for binary-input binary-output channels

Moskowitz, Ira S.; Cotae, Paul; Safier, Pedro N.

doi:10.1109/ciss.2012.6310786

Cited by 3 publications

(7 citation statements)

References 15 publications

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“…This paper continues the work of [21], wherein algebraic information theory is used to analyze SR. Before the algebraic approach to study the relationships between algebraic values of the channel matrix (such as the determinant), there did not exist any systematic way to compare the channel capacity of similar channels. The power of the algebraic approach, as put forth in [21], is exploited here to obtain results in SR. Similar thoughts were put forward by Telatar concerning MIMO channels [22].…”

Section: Why Algebraic Information Theorymentioning

confidence: 63%

“…For the (2,2) channel given by (a, b) the mutual information [9] is (this subsection borrows freely from [21])…”

Section: Information Theory For (22) Hannelsmentioning

confidence: 99%

“…We have shown in [21] how the Chapeau-Blondeau formulation can be easily normalized into Kosko's formulation. 3 Kosko [3] uses < and ≥, the difference is trivial except for a boundary point.…”

Section: Channel Matrix Mmentioning

confidence: 99%

“…In brief, AIT is the idea of using algebraic properties of the channel matrix such as the determinant and eigenvalues [27] to glean knowledge about the channel capacity. AIT has been used in [21] a < a =⇒ C(a, b) < C(a , b), and…”

Section: Algebraic Information Theorymentioning

confidence: 99%

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Algebraic Information Theory and Kosko's Forbidden Interval Theorem

Moskowitz¹,

Safier²,

Cotae³

2013

Modelling, Identification and Control / 801: Advances in Computer Science

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We introduce a more general definition of stochastic resonance in the context of algebraic information theory. By focusing on discrete memoryless communication channels with threshold, we reformulate Kosko's forbidden interval theorem in an algebraic manner. Based on our definition of stochastic resonance, we derive an analytic expression of the Shannon capacity for noisy binary-input, binary output discrete memoryless channels. Our analytic results agree with the algebraic information theory ordering theorem.

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Section: Why Algebraic Information Theorymentioning

confidence: 63%

“…For the (2,2) channel given by (a, b) the mutual information [9] is (this subsection borrows freely from [21])…”

Section: Information Theory For (22) Hannelsmentioning

confidence: 99%

Section: Channel Matrix Mmentioning

confidence: 99%

Section: Algebraic Information Theorymentioning

confidence: 99%

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Algebraic Information Theory and Kosko's Forbidden Interval Theorem

Moskowitz¹,

Safier²,

Cotae³

2013

Modelling, Identification and Control / 801: Advances in Computer Science

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“…Various performance metrics in the presence of SR such as signal to noise ratio, mutual information, and channel capacity improvement under a certain range of power noise levels, were discussed in [2]. In [9], [13] and [14], the SR effect is observed on the binary-input binaryoutput (2,2) DMC capacity, where maximum capacity occurs at an optimal power (variance) value of the AGN in relation to a given threshold level.…”

Section: Introductionmentioning

confidence: 99%

Threshold based Stochastic Resonance for the Binary-Input Ternary-Output Discrete Memoryless Channels

Kamdem¹,

Cotae²,

Moskowitz³

2012

Imaging and Signal Processing in Health Care and Technology / 772: Human-Computer Interaction / 773: Communication, Internet An

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Mutual Information and Multi-Agent Systems

Moskowitz

Rogers

Russell

2022

Entropy

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We consider the use of Shannon information theory, and its various entropic terms to aid in reaching optimal decisions that should be made in a multi-agent/Team scenario. The methods that we use are to model how various agents interact, including power allocation. Our metric for agents passing information are classical Shannon channel capacity. Our results are the mathematical theorems showing how combining agents influences the channel capacity.

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Algebraic information theory and stochastic resonance for binary-input binary-output channels

Cited by 3 publications

References 15 publications

Algebraic Information Theory and Kosko's Forbidden Interval Theorem

Algebraic Information Theory and Kosko's Forbidden Interval Theorem

Threshold based Stochastic Resonance for the Binary-Input Ternary-Output Discrete Memoryless Channels

Mutual Information and Multi-Agent Systems

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