Combining Artificial Neural Nets

Combining Artificial Neural Nets Ensemble and Modular Multi-Net Systems - Perspectives in Neural Computing

1st Edition.

Paperback (22 Jan 1999)

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Publisher's Synopsis

The past decade could be seen as the heyday of neurocomputing: in which the capabilities of monolithic nets have been well explored and exploited. The question then is where do we go from here? A logical next step is to examine the potential offered by combinations of artificial neural nets, and it is that step that the chapters in this volume represent. Intuitively, it makes sense to look at combining ANNs. Clearly complex biological systems and brains rely on modularity. Similarly the principles of modularity, and of reliability through redundancy, can be found in many disparate areas, from the idea of decision by jury, through to hardware re- dundancy in aeroplanes, and the advantages of modular design and reuse advocated by object-oriented programmers. And it is not surprising to find that the same principles can be usefully applied in the field of neurocomput- ing as well, although finding the best way of adapting them is a subject of on-going research.

Book information

ISBN: 9781852330040
Publisher: Springer London
Imprint: Springer
Pub date:
Edition: 1st Edition.
DEWEY: 006.32
DEWEY edition: 21
Language: English
Number of pages: 298
Weight: 482g
Height: 234mm
Width: 156mm
Spine width: 16mm