CMU Artificial Intelligence Repository
GRADSIM: Connectionist Network Optimization Package
areas/neural/systems/gradsim/
GRADSIM is a connectionist network optimization package, a neural
network simulator that supports recurrent time-delay network
optimization. GRADSIM was designed for simulation experiments with
the temporal flow model and was developed for research in speech
recognition. The temporal flow model is characterized by delay links
and unrestricted network connectivity. The simulator accepts network
descriptors and experiment descriptors in a very simple format, and
efficiently computes the complete gradient of recurrent networks. It
can be configured for several gradient descent methods.
Origin:
linc.cis.upenn.edu:/pub/gradsim.v2.tar.Z
Version: 2.0 (8-OCT-90)
Requires: C
Copying: Copyright (C) 1988, Trustees of the University of Pennsylvania.
Copyright (C) 1990, Trustees of the University of Toronto.
Use, copying, and distribution permitted, provided it
is not sold for profit.
CD-ROM: Prime Time Freeware for AI, Issue 1-1
Author(s): Raymond Watrous
Siemens Corporate Research
755 College Road East
Princeton, NJ 08540
Tel: (609) 734-6596
Keywords:
Authors!Watrous, GRADSIM, Gradient Descent,
Machine Learning!Neural Networks, Neural Networks!Simulators,
Recurrent Neural Networks, Speech Recognition,
Temporal Flow Model, Time Delay Neural Networks,
Univ. of Pennsylvania, Univ. of Toronto
References: ?
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