Title :
Analog implementation of neural networks
Author :
Zurada, Jacek M.
Author_Institution :
Dept. of Electr. Eng., Louisville Univ., KY, USA
Abstract :
Analog silicon-based neural hardware, which represents a large category among special-purpose analog and digital neurocomputers, and neural processing algorithms are reviewed. Artificial neural networks usually contain a large number of synaptic connections and many fewer processing neurons. The central problem in implementing artificial neural networks-making weights that are continuously adjustable, preferably in response to an analog control signal-is discussed. A simple integrated-circuit analog multiplier built from all-MOS components for use in electrically tunable synapses is described.<>
Keywords :
MOS integrated circuits; analogue computer circuits; multiplying circuits; neural nets; MOS components; adjustable weights; analog control signal; analogue implementation; electrically tunable synapses; integrated-circuit analog multiplier; neural networks; neural processing algorithms; neurocomputers; synaptic connections; Arithmetic; Artificial neural networks; Computer networks; Computer vision; Concurrent computing; Embedded computing; Neural network hardware; Neural networks; Neurons; Very large scale integration;
Journal_Title :
Circuits and Devices Magazine, IEEE
