A multi-dimensional analog Gaussian radial basis circuit

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).