The activation dynamics of nets are considered from a rigorous mathematical point of view.
A net is identified with the dynamical system defined by a continuously differentiable vector …

The exact form of a gradient-following learning algorithm for completely recurrent networks
running in continually sampled time is derived and used as the basis for practical algorithms …

INTRODUCTION TO THE THEORY OF NEURAL COMPUTATION Page 1 Page 2
INTRODUCTION TO THE THEORY OF NEURAL COMPUTATION Page 3 Page 4 …

Intelligent agents are employed as the central characters in this introductory text. Beginning
with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to …

Connectionist Speech Recognition: A Hybrid Approach describes the theory and
implementation of a method to incorporate neural network approaches into state of the art …

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NEURAL NETWORK FUNDAMENTALS WITH GRAPHS, ALGORITHMS, AND APPLICATIONS
Page 1 NEURAL NETWORK FUNDAMENTALS WITH GRAPHS, ALGORITHMS, AND …

In this two-part series, the writers investigate the role of artificial neural networks (ANNs) in
hydrology. ANNs are gaining popularity, as is evidenced by the increasing number of papers …

The real-time recurrent learning algorithm is a gradient-following learning algorithm for
completely recurrent networks running in continually sampled time. Here we use a series of …

1.1 Overview We are living in a decade recently declared as the" Decade of the Brain".
Neuroscientists may soon manage to work out a functional map of the brain, thanks to …