Title :
A scalable low voltage 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
fDate :
11/1/1997 12:00:00 AM
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 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. Our design is hierarchical and the number of transistors scales almost linearly with the input dimension making it amenable to VLSI implementation
Keywords :
CMOS analogue integrated circuits; VLSI; analogue processing circuits; neural chips; Gaussian basis function networks; VLSI implementation; analog Gaussian radial basis circuit; hardware implementation; hierarchical design; large fan-in; learning algorithms; localized receptive field units; scalable low voltage analog circuit; Application software; Biological neural networks; Circuit simulation; Computer vision; Detectors; Hardware; Input variables; Low voltage; Neurons; Very large scale integration;
Journal_Title :
Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on