DocumentCode :
1983592
Title :
Non-linear circuit effects on analog VLSI neural network implementations
Author :
Onorato, M. ; Valle, M. ; Caviglia, D.D. ; Bisio, G.M.
Author_Institution :
Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy
fYear :
1994
fDate :
26-28 Sep 1994
Firstpage :
430
Lastpage :
438
Abstract :
We present an analog VLSI neural network for texture analysis; in particular we show that the filtering block, which is the most critical block of the architecture for precision of computation, can be implemented using simple and compact analog circuits, without significant loss in classification performance. Through an accurate analysis of the circuits it is possible to model the real circuit characteristics in the software simulation environment; the weights calculated in the learning phase (which is performed off-line using the adaptive simulated annealing algorithm), can be properly coded into analog circuit variables in order to implement the correct operation of the network
Keywords :
analogue multipliers; adaptive simulated annealing algorithm; analog VLSI neural network; analog circuit variables; circuit characteristics modeling; classification performance; filtering block; learning phase; software simulation environment; surface defect detection; synaptic multiplier model; texture analysis; Analog circuits; Analog computers; Analytical models; Circuit analysis computing; Circuit simulation; Computer architecture; Filtering; Neural networks; Performance analysis; Very large scale integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Microelectronics for Neural Networks and Fuzzy Systems, 1994., Proceedings of the Fourth International Conference on
Conference_Location :
Turin
Print_ISBN :
0-8186-6710-9
Type :
conf
DOI :
10.1109/ICMNN.1994.593739
Filename :
593739
Link To Document :
بازگشت