Path: utzoo!utgpu!watserv1!watmath!att!att!news.cs.indiana.edu!noose.ecn.purdue.edu!samsung!think.com!sdd.hp.com!uakari.primate.wisc.edu!aplcen!jhunix!ins_atge From: ins_atge@jhunix.HCF.JHU.EDU (Thomas G Edwards) Newsgroups: comp.ai.neural-nets Subject: Re: Defining a Nerual Network Message-ID: <6904@jhunix.HCF.JHU.EDU> Date: 17 Nov 90 02:48:49 GMT References: <2491@bimacs.BITNET> Organization: The Johns Hopkins University - HCF Lines: 24 Summary:soft definitions for soft classifiers In article <2491@bimacs.BITNET> guedalia@bimacs.BITNET (David Guedalia) writes: >Hi, > Has anyone seen or heard a definition for a Neural Network. Not really. In the literature, and talking with researchers, you will here "neural network" associated with almost any kind of real-valued massively parallel computations which are used to perform AI tasks. More formally, however, "neural network" is usually reserved for real brain circuitry (as opposed to "artificial neural network", reserved for massively parallel networks which people think up and program/build). The tem used for the field of working with artificial neural networks is refered to as "connectionism," which makes one envisioned interesting computation done by interconnected elements. Kohonen maps can fall into the "connectionist" label fairly well. The moral of the story here is that there are no hard-and-fast definitions of these terms, which is totally apt for the "fuzzy" and fault-tolerant nature of neural nets. -Thomas Edwards