Title :
Analog integrate-and-fire neurochips: neural competition in frequency and time domains
Author :
Asai, Tetsuya ; Hayashi, Hideki ; Amemiya, Yoshihito
Author_Institution :
Dept. of Electr. Eng., Hokkaido Univ., Sapporo, Japan
Abstract :
In this report, we present all inhibitory neural network, implemented on analog CMOS chips, that exhibits competitive behaviors in the frequency and time domains. The circuit for each neuron was designed to produce sequences in time of identically-shaped pulses, called spikes. The result of experiment and simulation revealed that the network more efficiently achieved the selective activation and inactivation of the neuron circuits on the basis of spike timing rather than of firing rates. The results indicate that the spike-timing-based neural processing by spiking neuron circuits provides a possible way of overcoming low tolerance problems of analog devices in noisy environments.
Keywords :
CMOS analogue integrated circuits; VLSI; frequency-domain analysis; neural chips; time-domain analysis; VLSI; analog CMOS chips; competitive neural network; firing rates; frequency domains; integrate-and-fire neural chips; spike-timing code; spiking neuron circuits; time domains; Artificial neural networks; Biological neural networks; Biomembranes; Circuits; Nervous system; Neurons; Silicon; Timing; Very large scale integration; Working environment noise;
Conference_Titel :
Automation Congress, 2002 Proceedings of the 5th Biannual World
Print_ISBN :
1-889335-18-5
DOI :
10.1109/WAC.2002.1049533