1. A signal processing apparatus using a neural network, comprising: reference signal generating means for generating a plurality of reference signals each having different signal values; complement signal generating means for receiving the reference signals, and an input signal as an object to be processed, and generating a plurality of complement signals indicating complement values of the reference signals by obtaining a first product by multiplying the input signal with a natural number and mathematically combining said first product with said reference signals; multiplication means for receiving the reference signals and the complement signals, and multiplying the reference signals with the corresponding complement signals, thereby obtaining second products; and a neural network, in which a plurality of neurons are suppression-mutual-coupled, said neurons receive the second products obtained by said multiplication means, and one of said neurons which receives the second product having a largest value outputs a spark signal; wherein an analog signal is input as the input signal, and said reference signal generating means generates analog signals as the reference signals; wherein said reference signal generating means comprises means for generating N reference analog signals whose signal values have a relationship of an arithmetic sequence, said neural network outputs the spark signal from the neuron, which is applied with the reference signal most approximate to the input signal, and said apparatus further comprises sense means for detecting the neuron which outputs the spark signal, and converting the input signal into an N-ary 1-digit digital signal according to the detected sparking neuron