ferris@eniac.seas.upenn.edu (Richard T. Ferris) (03/15/90)
In article <2945@umbc3.UMBC.EDU> bruce@atria.gsfc.nasa.gov (Bruce Mount) writes: >I, too, would like *ANY* suggestions for a beginning book on neural nets. >Something like "Neural nets for idiots" or "Neural nets made so simple >even YOU can understand it". In addition to the Huge amount of info in the recent issues of most computer magazines (Dr. Dobbs, etc) try a book called Neural Computing written by Philip D. Wasserman and published by Van Norstrand Reinhold c1989. The book covers a lot of the basics. P. 38 of the April issue of Dr. Dobbs has a nice introductory article. RF Richard T. Ferris ferris@eniac.seas.upenn.edu University of Pennsylvania
smb@datran2.uunet (Steven M. Boker) (03/16/90)
In article <21740@netnews.upenn.edu>, ferris@eniac.seas.upenn.edu (Richard T. Ferris) writes: > > In article <2945@umbc3.UMBC.EDU> bruce@atria.gsfc.nasa.gov (Bruce Mount) writes: > >I, too, would like *ANY* suggestions for a beginning book on neural nets. > >Something like "Neural nets for idiots" or "Neural nets made so simple > >even YOU can understand it". > I've spent the last couple of years reading around in the field. In January I read a new one called "Neural Computing: Theory and Practice" by Wasserman. I believe its Holt Reinhart if my own net is still holding up. This book is written for someone that wants to understand the basics of all of the current theories. Their strengths and weakness and what makes one net different from another (this sentence no verb). Wasserman has gone to a good deal of trouble to make the diagrammatic style of applied to each network uniform so that the differences in topology are what stands out. Hope that made sense, this terminal has the arrow keys mapped to something that this editor doesnt understand. Wasserman's insights into each network system are, to my mind, right on target. And for those who find matrix notation obscure, he's included the five minutes up to speed guide to matrix algebra. All in all, its easily the best intro I've seen. Next step would be Rumelhart & McClelland. Thats the classic of the eighties as far as I can see. The Neurocomputing book is a great survey of the literature going back to William James. Neurocomputing: Foundations of Research, Anderson & Rosenfeld. For the ART perspective you might give a shot at Stephen Grossberg's Neural Networks and Natural Intelligence. Good luck. Steve. -- #====#====#====#====#====#====#====#====#====#====#====#====#====#====#====# # Steve Boker # Black holes are how God divides by zero. # # smb@datran2.uunet.uu.net # ....I have my own methods. # #====#====#====#====#====#====#====#====#====#====#====#====#====#====#====#