Paper available: KBANN applied to ECG processing

[Raymond L Watrous]

	FTP-HOST: scr.siemens.com
	FTP-filename: /pub/learning/Papers/watrous/soar.ps.Z

The following paper (7 pages, 3 figures) is now available via
anonymous ftp:

     Synthesize, Optimize, Analyze, Repeat (SOAR): Application
	  of Neural Network Tools to ECG Patient Monitoring

		Raymond Watrous, Geoffrey Towell
		   and Martin S. Glassman

		 Siemens Corporate Research
		 755 College Road East
		 Princeton, NJ 08540

			Abstract

Results are reported from the application of tools for synthesizing,
optimizing and analyzing neural networks to an ECG Patient Monitoring
task. A neural network was synthesized from a rule-based classifier
and optimized over a set of normal and abnormal heartbeats. The
classification error rate on a separate and larger test set was
reduced by a factor of 2. Sensitivity analysis of the synthesized and
optimized networks revealed informative differences. Analysis of the
weights and unit activations of the optimized network enabled a
reduction in size of the network by a factor of 40% without loss of
accuracy.

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The paper will appear in the Proceedings of the Workshop on
Environmental and Energy Applications of Neural Networks, March 30-31,
1995, Richland, Washington, and is reprinted from the Proceedings of
the Third International Congress on Air- and Structure-Borne Sound and
Vibration, June 13-15, 1994, Montreal, Quebec, pp. 997-1004, and the
Proceedings of the 1993 Symposium on Nonlinear Theory and its
Applications, December 5-10, Honolulu, Hawaii, pp. 565-570.

We regret that we are unable to provide hard copies.

Raymond Watrous

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Learning Systems Department		Phone: (609) 734-6596
Siemens Corporate Research		FAX:   (609) 734-6565
755 College Road East
Princeton, NJ 08540

watrous at learning.scr.siemens.com