Title :
A simulation and training technique for analog neural network implementations
Author :
Mundie, David B. ; Massengill, Lloyd W.
Author_Institution :
Dept. of Electr. Eng., Memphis State Univ., TN, USA
fDate :
27 Jun-2 Jul 1994
Abstract :
A neural network simulation technique tailored for analog hardware implementation is discussed. Lookup tables are used to represent the nonideal properties of the analog circuitry. A weight perturbation training algorithm, well suited for hardware implementations, is presented. Simulated annealing schemes are shown to improve training performance associated with analog neural networks
Keywords :
analogue processing circuits; circuit analysis computing; learning (artificial intelligence); neural nets; table lookup; analog circuitry; analog neural network; lookup tables; neural network simulation; simulated annealing; training; weight perturbation training algorithm; Analog circuits; Artificial neural networks; Circuit simulation; Computational modeling; Dynamic range; Neural network hardware; Neural networks; Pulse modulation; SPICE; Table lookup;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374464
