Title :
A multi-dimensional analog Gaussian radial basis circuit
Author :
Theogarajan, Luke ; Akers, L.A.
Author_Institution :
Center for Solid State Electron. Res., Arizona State Univ., Tempe, AZ, USA
Abstract :
Gaussian basis function (GBF) networks are powerful systems for learning and approximating complex input-output mappings. Networks composed of these localized receptive field units trained with efficient learning algorithms have been simulated solving a variety of interesting problems. For real-time and portable applications however, direct hardware implementation is needed. We describe simulated and experimental results from the most compact, low voltage analog Gaussian basis circuit yet reported. We also extend our circuit to handle large fan-in with minimal additional hardware. We show a SPICE simulation of our circuit implementing a multivalued exponential associative memory (MERAM)
Keywords :
CMOS analogue integrated circuits; analogue processing circuits; content-addressable storage; neural chips; real-time systems; recurrent neural nets; CMOS chip; Gaussian basis function networks; Gaussian radial basis circuit; compact low voltage circuit; complex input-output mappings approximation; large fan-in; multi-dimensional analog GBF circuit; multivalued exponential associative memory; portable applications; real-time applications; Application software; Circuit simulation; Correlators; Differential amplifiers; Electronic mail; Hardware; Lakes; Low voltage; Signal processing algorithms; Solid state circuits;
Conference_Titel :
Circuits and Systems, 1996. ISCAS '96., Connecting the World., 1996 IEEE International Symposium on
Print_ISBN :
0-7803-3073-0
DOI :
10.1109/ISCAS.1996.541653