Proceedings Paper
Universal 2-layered noniterative perceptron for recognizing closely related patterns| Format | Member Price | Non-Member Price |
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Paper Abstract
As we published in the last eight years, when the analog-to- binary mapping of any M training CLASS patterns are not PLI, then a one-layered preceptron (OLP) just cannot learn this mapping at all no matter what learning rule we use, because the solution of the connection matrix does not exist. However, as we derived form this PLI condition, which is the most general separability condition for an OLP, a PCTLP system can still be used to separate these closely relate and 'inseparable' patterns according to the targeted outputs Vm. This paper repots the theory and the design of this NOVEL PCTLP system.
Paper Details
Date Published: 4 August 2000
PDF: 6 pages
Proc. SPIE 4052, Signal Processing, Sensor Fusion, and Target Recognition IX, (4 August 2000); doi: 10.1117/12.395079
Published in SPIE Proceedings Vol. 4052:
Signal Processing, Sensor Fusion, and Target Recognition IX
Ivan Kadar, Editor(s)
PDF: 6 pages
Proc. SPIE 4052, Signal Processing, Sensor Fusion, and Target Recognition IX, (4 August 2000); doi: 10.1117/12.395079
Show Author Affiliations
Chia-Lun John Hu, Southern Illinois Univ./Carbondale (United States)
Published in SPIE Proceedings Vol. 4052:
Signal Processing, Sensor Fusion, and Target Recognition IX
Ivan Kadar, Editor(s)
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