Predictive Modular Neural Networks: Applications to Time Series

Predictive Modular Neural Networks: Applications to Time Series

by Vassilios Petridis, Athanasios Kehagias
     
 

This book presents a unified methodology for designing modular neural networks. A family of online algorithms for time series classification, prediction and identification are developed; and a rigorous mathematical analysis of their properties is provided. Case studies involving a number of real world problems are also presented. Finally, an overview of the modular… See more details below

Overview

This book presents a unified methodology for designing modular neural networks. A family of online algorithms for time series classification, prediction and identification are developed; and a rigorous mathematical analysis of their properties is provided. Case studies involving a number of real world problems are also presented. Finally, an overview of the modular neural networks literature, including coverage of theoretical and experimental analysis, is provided. Predictive Modular Neural Networks: Applications to Time Series is an important reference work for engineers, computer scientists, and other researchers working in time series analysis, neural networks, control engineering, data mining and other intelligent and decision support areas. The book will also be of interest to researchers in biological and medical informatics.

Product Details

ISBN-13:
9781461375401
Publisher:
Springer US
Publication date:
04/30/2013
Series:
Springer International Series in Engineering and Computer Science, #466
Edition description:
Softcover reprint of the original 1st ed. 1998
Pages:
314
Product dimensions:
6.14(w) x 9.21(h) x 0.69(d)

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