Nonlinear Noise Cancellation Based on Fuzzy T-S Model
Sun Li-ping · Jisuanji fangzhen · 2007
Additive noise may produce adverse influence on system identification. However, an output of a real system is often affected by noise. Noise canceling by using fuzzy inference system is studied. A kind of nonlinear noise cancellation algorithm based on T-S fuzzy model is proposed. The structure of nonlinear noise cancellation (NNC) and the theory of noise canceling are described. Fuzzy rules are obtained from the input-output data pairs. The value of the fuzzy rule’s consequent is calculated by recursive least square (RLS) method. At last the useful signal is received by subtracting the noise from measuring signal. The simulation results show that fuzzy inference system can be successfully applied to noise cancellation.