DocumentCode
3276670
Title
Performance analysis and application of the bidirectional associative memory to industrial spectral signatures
Author
Mathai, G. ; Upadhyaya, B.R.
Author_Institution
Dept. of Nucl. Eng., Tennessee Univ., Knoxville, TN, USA
fYear
1989
fDate
0-0 1989
Firstpage
33
Abstract
A detailed study of the performance of the bidirectional associative memory (BAM) for the classification of power spectral density (PSD) functions is presented. The BAM has error-correcting properties and is capable of generating a successful recall, even with noisy and incomplete patterns. Suitable pattern coding schemes are utilized to enhance the discriminating features in the patterns. A bit-mapping scheme is used to construct binary pattern vectors from the PSD. The numerical aspects of signature encoding and fault tolerance property of the BAM are evaluated using spectral density functions of signals from a fiber-manufacturing rotating machinery system. The results of the application of the BAM are superior to those obtained with classical pattern recognition methods.<>
Keywords
content-addressable storage; neural nets; pattern recognition; spectral analysis; bidirectional associative memory; binary pattern vectors; bit-mapping scheme; discriminating features; error-correcting properties; fault tolerance property; feature enhancement; fiber-manufacturing rotating machinery system; incomplete patterns; industrial spectral signatures; noise; pattern coding schemes; pattern recognition; performance analysis; power spectral density function classification; signature encoding; Associative memories; Neural networks; Pattern recognition; Spectral analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1989. IJCNN., International Joint Conference on
Conference_Location
Washington, DC, USA
Type
conf
DOI
10.1109/IJCNN.1989.118556
Filename
118556
Link To Document