NEURAL COMPUTATION 9:2

[Terry Sejnowski]

Neural Computation -  Contents Volume 9, Number 2 - February 15, 1997

Review

Probabilistic Independence Networks for Hidden Markov Probability Models
	Padhraic Smyth, David Heckerman, and Michael I. Jordan
		
Note

Using Expectation-Maximization for Reinforcement Learning
	Peter Dayan and Geoffrey E. Hinton
		
Letter

Fast Sigmoidal Networks via Spiking Neurons
	Wolfgang Maass

Computing with the Leaky Integrate-and-Fire Neuron: Logarithmic 	
Computation and Multiplication
	Doron Tal and Eric L. Schwartz

Effect of Delay on the Boundary of the Basin of Attraction in a
Self-Excited Single Graded-Response Neuron
	K. Pakdaman, C. Grotta-Ragazzo, C. P. Malta, and J.-F. Vibert

Shattering All Sets of 'K' Points in "General Position" Requires 
(K-1)/2 Parameters
	Eduardo D. Sontag

Statistical Inference, Occam's Razor and Statistical Mechanics on the 	
Space of Probability Distributions
	Vijay Balasubramanian
		
Bias/Variance Analyses of Mixtures-of-Experts Architectures
	Robert A. Jacobs
		
The Behavior of Forgetting Learning in Bidirectional Associative Memory
	Chi Sing Leung and Lai Wan Chan

Adaptive Encoding Strongly Improves Function Approximation with CMAC
	Martin Eldracher, Alexander Staller, and Rene Pompl

An Analog Memory Circuit for Spiking Silicon Neurons
	John G. Elias, David P. M. Northmore, and Wayne Westerman
	
Average-Case Learning Curves for Radial Basis Function Networks
	Sean B. Holden and Mahesan Niranjan
		
A Sequential Learning Scheme for Function Approximation Using 	
Minimal Radial Basis Function Neural Networks
	Lu Yingwei, N. Sundararajan, and P. Saratchandran
		
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