The Springer International Engineering and Computer Science

A Neural-Based Paradigm

By: Enrique Castillo, Angel Cobo, Jose Antonio Gutierrez

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Hardcover | 31 October 1998

At a Glance

Hardcover
328 Pages

Dimensions(cm)
24.13 x 16.51 x 1.91

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$169.00

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This book introduces `functional networks', a novel neural-based paradigm, and shows that functional network architectures can be efficiently applied to solve many interesting practical problems.
Included is an introduction to neural networks, a description of functional networks, examples of applications, and computer programs in Mathematica and Java languages implementing the various algorithms and methodologies.
Special emphasis is given to applications in several areas such as:

Box-Jenkins AR(p), MA(q), ARMA(p,q), and ARIMA (p,d,q) models with application to real-life economic problems such as the consumer price index, electric power consumption and international airlines' passenger data. Random time series and chaotic series are considered in relation to the H‚non, Lozi, Holmes and Burger maps, as well as the problems of noise reduction and information masking.
Learning differential equations from data and deriving the corresponding equivalent difference and functional equations. Examples of a mass supported by two springs and a viscous damper or dashpot, and a loaded beam, are used to illustrate the concepts.
The problem of obtaining the most general family of implicit, explicit and parametric surfaces as used in Computer Aided Design (CAD).
Applications of functional networks to obtain general nonlinear regression models are given and compared with standard techniques.

Functional Networks with Applications: A Neural-Based Paradigm will be of interest to individuals who work in computer science, physics, engineering, applied mathematics, statistics, economics, and other neural networks and data analysis related fields.

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Preface
Neural Networks	p. 1
Introduction to Neural Networks	p. 5
Functional Networks	p. 47
Introduction to Functional Networks	p. 51
Functional Equations	p. 71
Some Functional Network Models	p. 97
Model Selection	p. 133
Applications	p. 147
Applications to Time Series	p. 151
Applications to Differential Equations	p. 195
Applications to CAD	p. 221
Applications to Regression	p. 239
Computer Programs	p. 259
Mathematica Programs	p. 263
A Java Applet	p. 283
Notation	p. 291
References	p. 299
Index	p. 305
Table of Contents provided by Blackwell. All Rights Reserved.

The Springer International Engineering and Computer Science

A Neural-Based Paradigm

At a Glance

Hardcover

Shipping

How to return your order

Defective items

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Paperback

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