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Volume 9, Issue 2

February 1997

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ISSN 0899-7667

EISSN 1530-888X

In this Issue

Review
Note
Letters

Review

Probabilistic Independence Networks for Hidden Markov Probability Models

Padhraic Smyth, David Heckerman, Michael I. Jordan

Neural Computation (1997) 9 (2): 227–269.

Abstract

View articletitled, Probabilistic Independence Networks for Hidden Markov Probability Models

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Note

Using Expectation-Maximization for Reinforcement Learning

Peter Dayan, Geoffrey E. Hinton

Neural Computation (1997) 9 (2): 271–278.

Abstract

View articletitled, Using Expectation-Maximization for Reinforcement Learning

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Letters

Fast Sigmoidal Networks via Spiking Neurons

Wolfgang Maass

Neural Computation (1997) 9 (2): 279–304.

Abstract

View articletitled, Fast Sigmoidal Networks via Spiking Neurons

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Computing with the Leaky Integrate-and-Fire Neuron: Logarithmic Computation and Multiplication

Doron Tal, Eric L. Schwartz

Neural Computation (1997) 9 (2): 305–318.

Abstract

View articletitled, Computing with the Leaky Integrate-and-Fire Neuron: Logarithmic Computation and Multiplication

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Effect of Delay on the Boundary of the Basin of Attraction in a Self-Excited Single Graded-Response Neuron

K. Pakdaman, C. P. Malta, C. Grotta-Ragazzo, J.-F. Vibert

Neural Computation (1997) 9 (2): 319–336.

Abstract

View articletitled, Effect of Delay on the Boundary of the Basin of Attraction in a Self-Excited Single Graded-Response Neuron

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Shattering All Sets of ‘k’ Points in “General Position” Requires (k — 1)/2 Parameters

Eduardo D. Sontag

Neural Computation (1997) 9 (2): 337–348.

Abstract

View articletitled, Shattering All Sets of <em>‘k’</em> Points in “General Position” Requires (<em>k</em> — 1)/2 Parameters

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Statistical Inference, Occam's Razor, and Statistical Mechanics on the Space of Probability Distributions

Vijay Balasubramanian

Neural Computation (1997) 9 (2): 349–368.

Abstract

View articletitled, Statistical Inference, Occam's Razor, and Statistical Mechanics on the Space of Probability Distributions

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Bias/Variance Analyses of Mixtures-of-Experts Architectures

Robert A. Jacobs

Neural Computation (1997) 9 (2): 369–383.

Abstract

View articletitled, Bias/Variance Analyses of Mixtures-of-Experts Architectures

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The Behavior of Forgetting Learning in Bidirectional Associative Memory

Chi Sing Leung, Lai Wan Chan

Neural Computation (1997) 9 (2): 385–401.

Abstract

View articletitled, The Behavior of Forgetting Learning in Bidirectional Associative Memory

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Adaptive Encoding Strongly Improves Function Approximation with CMAC

Martin Eldracher, Alexander Staller, René Pompl

Neural Computation (1997) 9 (2): 403–417.

Abstract

View articletitled, Adaptive Encoding Strongly Improves Function Approximation with CMAC

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An Analog Memory Circuit for Spiking Silicon Neurons

John G. Elias, David P. M. Northmore, Wayne Westerman

Neural Computation (1997) 9 (2): 419–440.

Abstract

View articletitled, An Analog Memory Circuit for Spiking Silicon Neurons

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Average-Case Learning Curves for Radial Basis Function Networks

Sean B. Holden, Mahesan Niranjan

Neural Computation (1997) 9 (2): 441–460.

Abstract

View articletitled, Average-Case Learning Curves for Radial Basis Function Networks

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A Sequential Learning Scheme for Function Approximation Using Minimal Radial Basis Function Neural Networks

Lu Yingwei, N. Sundararajan, P. Saratchandran

Neural Computation (1997) 9 (2): 461–478.

Abstract

View articletitled, A Sequential Learning Scheme for Function Approximation Using Minimal Radial Basis Function Neural Networks

Review

Probabilistic Independence Networks for Hidden Markov Probability Models

Note

Using Expectation-Maximization for Reinforcement Learning

Letters

Fast Sigmoidal Networks via Spiking Neurons

Computing with the Leaky Integrate-and-Fire Neuron: Logarithmic Computation and Multiplication

Effect of Delay on the Boundary of the Basin of Attraction in a Self-Excited Single Graded-Response Neuron

Shattering All Sets of ‘k’ Points in “General Position” Requires (k — 1)/2 Parameters

Statistical Inference, Occam's Razor, and Statistical Mechanics on the Space of Probability Distributions

Bias/Variance Analyses of Mixtures-of-Experts Architectures

The Behavior of Forgetting Learning in Bidirectional Associative Memory

Adaptive Encoding Strongly Improves Function Approximation with CMAC

An Analog Memory Circuit for Spiking Silicon Neurons

Average-Case Learning Curves for Radial Basis Function Networks

A Sequential Learning Scheme for Function Approximation Using Minimal Radial Basis Function Neural Networks

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