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NN-Simulator: Flexible and User-Friendly Neural Network Simulator

The simulate program is a user-friendly and flexible neural network simulator. It is designed to handle the simulation of associative learning style networks, such as the LMS (aka Rescorla-Wagner) learning procedure and Backpropagation. Multiple interacting networks can be simulated in parallel, with their behavior and interactions specified by a simple command language. Some of the more useful features of the simulator include: - Simulation weights can be saved, and later used to initialize the weights of a new simulation. - Multilayer networks with arbitrary interconnectivity can be created. - Quickprop, a faster version of backpropagation is supported. - Network behavior on each cycle in the simulation can be specified. - The output of the simulation on each cycle can be specified. The example network files include: - ENCODER. Simulation files for a 10-5-10 encoder (described in (Rumelhart & McClelland, 1986 v.1). Demonstrates a simple backpropagation network. - HINTON. Simulation files for Hinton's "family tree problem" (Hinton, 1986). This demonstrates a more sophisticated example of backpropagation: the network is six layers instead of 3. Includes both backprop and quickprop versions of the network. - SHANKS. Simulation files for some simple linear associative networks (discussed in Shanks, 1991).
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Version: 26-JUN-93 Requires: C CD-ROM: Prime Time Freeware for AI, Issue 1-1 Author(s): Eric Melz UCLA Department of Psychology Franz Hall, UCLA Los Angeles, CA, 90024 USA Tel: (310) 825-8712 Keywords: Associative Learning Networks, Authors!Melz, Backpropagation, C!Code, LMS Learning Procedure, Linear Associative Networks, Machine Learning!Neural Networks, Neural Networks!Simulators, Quickprop, Rescorla-Wagner Learning Procedure References: ?
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