A reconfigurable 'ANN' architecture

Proposes a design of a digital artificial neural network (ANN). The architecture is based on a single-instruction multiple-data (SIMD) processing configuration. Communication is done through broadcasting and also by systolic methods. With the help of a microprogrammed control unit, the design is mainly capable of implementing the following three models: (1) Hamming, (2) Hopfield, and (3) Carpenter/Grossberg algorithms. The architecture was also designed to achieve parallelism, modularity, adaptability, flexibility, speed, low cost, smaller silicon area, and expandability.<
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