DocumentCode
2831807
Title
Implementation of a Kohonen map with learning capabilities
Author
Peiris, V. ; Hochet, B. ; Abdo, S. ; Declercq, M.
Author_Institution
Electron. Lab., Swiss Federal Inst. of Technol., Lausanne, Switzerland
fYear
1991
fDate
11-14 Jun 1991
Firstpage
1501
Abstract
An efficient and compact implementation of Kohonen neural networks with learning capability is described. Each synaptic weight is stored as a discrete voltage on a capacitor. The neurons compute the Manhattan distance between the input vector and their own synaptic vector using a dedicated arithmetics. The neighborhoods used during the learning phase are computed using a nonlinear resistor-based network
Keywords
CMOS integrated circuits; learning systems; neural nets; CMOS digital technology; Kohonen map; Kohonen neural networks; Manhattan distance; capacitor storage; dedicated arithmetics; discrete voltage; learning capabilities; neighborhoods; nonlinear resistor-based network; synaptic weight; Arithmetic; Capacitors; Circuits; Clocks; Hydrogen; Neural networks; Neurons; Vectors; Virtual colonoscopy; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1991., IEEE International Sympoisum on
Print_ISBN
0-7803-0050-5
Type
conf
DOI
10.1109/ISCAS.1991.176660
Filename
176660
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