Application of active noise control based on neural network to vehicle's engine sound

Active noise control(ANC) is a particularly effective system for reducing low-frequency noise to compensate passive noise control. With the recent development of digital signal processor(DSP) performance, ANC has the potential to be developed with various algorithms. Accordingly, several ANC algorithms using various controlloer such as artificial neural network(ANN) are being proposed. In nonlinear system; at many practical applications, the ANC algorithm using a neural network gets more reduction performance compared to the linear ANC. In this study, the methology proposed neural network based FxLMS algorithm to reduce noise for non-linear system by predicting time series data for near future. This proposed algorithm is applied to reduce the engine noise of vehicle to construct silent inner environment and verify the performance by below.