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Product Specifications
Book Summary
The first truly up-to-date look at the theory and capabilities of nonlinear
dynamical systems that take the form of feedforward neural network structures
Considered one of the most important types of structures in the study of neural
networks and neural-like networks, feedforward networks incorporating dynamical
elements have important properties and are of use in many applications.
Specializing in experiential knowledge, a neural network stores and expands its
knowledge base via strikingly human routes-through a learning process and
information storage involving interconnection strengths known as synaptic
weights.
In Nonlinear Dynamical Systems: Feedforward Neural Network Perspectives, six
leading authorities describe recent contributions to the development of an
analytical basis for the understanding
ISBN-13
9780471349112
Language
English
Binding
Hard Bound
Publisher
cbspd
Publishing Date
2001-02-21
Nonlinear Dynamical Systems: Feedforward Neural Network Perspectives (Adaptive and Learning Systems for Signal Processing, Communications and Control Series)
The first truly up-to-date look at the theory and capabilities of nonlinear
dynamical systems that take the form of feedforward neural network structures
Considered one of the most important types of structures in the study of neural
networks and neural-like networks, feedforward networks incorporating dynamical
elements have important properties and are of use in many applications.
Specializing in experiential knowledge, a neural network stores and expands its
knowledge base via strikingly human routes-through a learning process and
information storage involving interconnection strengths known as synaptic
weights.
In Nonlinear Dynamical Systems: Feedforward Neural Network Perspectives, six
leading authorities describe recent contributions to the development of an
analytical basis for the understanding