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NETS

General Information
Name
NETS - A NEURAL NETWORK DEVELOPMENT TOOL
Source
COSMIC The University of Georgia 382 East Broad Street Athens, GA 30602 U.S.A. Phone: (706) 542-3265 FAX: (706) 542-4807 Internet: service@cossack.cosmic.uga.edu
Price
International Price: Program 40.00
Target usage

Model

Network Architecture
Paradigms
NETS uses the back propagation learning method for all of the networks which it creates. The nodes of a network are usually grouped together into clumps called layers. Generally, a network will have an input layer through which the various environment stimuli are presented to the network, and an output layer for determining the network's response. The number of nodes in these two layers is usually tied to some features of the problem being solved. Other layers, which form intermediate stops between the input and output layers, are called hidden layers. NETS allows the user to customize the patterns of connections between layers of a network. NETS also provides features for saving the weight values of a network which allows for more precise control over the learning process.
Limitations
only backpropagation

Implementation

Display
User Interface
NETS is an interpreter. The user is presented with a prompt which is the simulator's way of asking for input. After a command is issued, NETS will attempt to evaluate the command, which may produce more prompts requesting specific information or an error if the command is not understood. The typical process involved when using NETS consists of translating the problem into a format which uses input/output pairs, designing a network configuration for the problem, and finally training the network with input/output pairs until an acceptable error is reached.
Execution
Data Format
files may be stored in binary or ASCII format
Evaluation
Performance

System Requirements

Hardware
IBM PC, Apple Macintosh, VAX, Sun, HP 9000
Operating System
Display
Language

Installation and Documentation

Installation
Sources available
Implementation language
C
Documentation
Support
User Groups



Previous: NERV
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franz@neuro.informatik.uni-ulm.de
Wed Jan 19 23:46:24 MET 1994