A digital fuzzy logic filter of type III interacts with a real model signal reference to obtain the best answer in the sense of minimum mean square error of the output. The key part of the filter is a fuzzy mechanism that adaptively selects and emits answer according to the changes of the external reference signal. Based on input signal level, this fuzzy filter selects the best parameter values from a set of membership in the knowledge base (KB), and the filter weights are updated according to the reference signal in a natural form. With this fuzzy structure the filter reduces error. The simulation result shows the stability of the filter. The states of the filtering process require that all of its answers are bounded by the error criteria probabilistically.
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