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    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
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Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems

Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems

Sharkey, Amanda J. C.

Paperback

Series: Perspectives in Neural Computing

General Computers

ISBN10: 185233004X
ISBN13: 9781852330040
Publisher: Springer Nature
Published: Jan 22 1999
Pages: 298
Weight: 1.06
Height: 0.77 Width: 6.15 Depth: 9.20
Language: English
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.

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