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This paper proposes a quantizer based on the Simple Hysteresis Network (SHN). The SHN is a hysteresis neural network in which all of the mutually coupled loads (neurons having hysteresis characteristics) are simplified. An A-D converter proposed by J. J. Hopfield uses neural networks, but this is highly initial-value-dependent so that the output for an arbitrary input is not necessarily satisfactory. The quantizer proposed in this paper guarantees the best output for an arbitrary analogue input. The proposed quantizer requires N wiring lines to obtain N bits of the output. This is significantly less than the A-D converter proposed by Hopfield, and practical circuits can easily be designed. © 1999 Scripta Technica, Electron Comm Jpn Pt 3, 83(4): 1–8, 2000
Jin et al. (Sat,) studied this question.