Research and Simulation on Adaptive Noise Cancellation System Based on BP Neural Network

Abstract:

Adaptive noise cancellation system can effectively eliminate interference, and has the strong nonlinear mapping capability and less calculation on the conditions of unknown outside interference source characteristics. Firstly, we research adaptive noise cancellation system principle and structure, and construct an adaptive noise cancellation system based on BP neural network combining with characteristics of BP neural network. Then we dynamically simulate the system using Simulink. The simulation results show that the model can effectively offset the noise signal of noise added signal.

• Periodical: Advanced Materials Research (Volume 580)
• Pages: 110-113
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.580.110
• Online since: October 2012
• Authors: Yan Ping He, Hai Dong Zhang, Ke Yan Deng
• Keywords: Adaptive Noise Cancellation System, BP Neural Network (BPNN), Simulink

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