Adaptive Modelling, Estimation and Fusion from Data

Adaptive Modelling, Estimation and Fusion from Data

by Qiang GanXia Hong and Chris Harris
Epub (Kobo), Epub (Adobe)
Publication Date: 20/05/2016
  $170.16

In a world of almost permanent and rapidly increasing electronic data availability, techniques of filtering, compressing, and interpreting this data to transform it into valuable and easily comprehensible information is of utmost importance. One key topic in this area is the capability to deduce future system behavior from a given data input.


This book brings together for the first time the complete theory of data-based neurofuzzy modelling and the linguistic attributes of fuzzy logic in a single cohesive mathematical framework. After introducing the basic theory of data-based modelling, new concepts including extended additive and multiplicative submodels are developed and their extensions to state estimation and data fusion are derived. All these algorithms are illustrated with benchmark and real-life examples to demonstrate their efficiency.


Chris Harris and his group have carried out pioneering work which has tied together the fields of neural networks and linguistic rule-based algortihms. This book is aimed at researchers and scientists in time series modeling, empirical data modeling, knowledge discovery, data mining, and data fusion.

ISBN:
9783642182426
9783642182426
Category:
Artificial intelligence
Format:
Epub (Kobo), Epub (Adobe)
Publication Date:
20-05-2016
Language:
English
Publisher:
Springer Berlin Heidelberg
Chris Harris

Chris Harris is a writer and executive producer for How I Met Your Mother and a writer for The Late Show with David Letterman.

His pieces have appeared in The New Yorker, Esquire, ESPN, The New York Times, The Wall Street Journal, and on NPR. He lives in Los Angeles.

This item is delivered digitally

Customer Reviews

Be the first to review Adaptive Modelling.