The Effects of Circuit Integration on a Feature Map Vector Quantizer
Jim Mann · Neural Information Processing Systems · 1989
The effects of parameter modifications imposed by hardware constraints on a self-organizing feature map algorithm were examined. Performance was measured by the error rate of a speech recognition system which included this algorithm as part of the front-end processing. System parameters which were varied included weight (connection strength) quantization, adaptation quantization, distance measures and circuit approximations which include device characteristics and process variability. Experiments using the TI isolated word database for 16 speakers demonstrated degradation in performance when weight quantization fell below 8 bits. The competitive nature of the algorithm relaxes constraints on uniformity and linearity which makes it an excellent candidate for a fully analog circuit implementation. Prototype circuits have been fabricated and characterized following the constraints established through the simulation efforts.