Wavelet-Based Neural Network Adaptive Filter for sEMG Denoising
For the large computation workload of the adaptive filter algorithm and the low filtering speed of the adaptive filter model based on wavelet transform, a wavelet-based neural network adaptive filter model is constructed in this paper. As the neural network has the capacity of distributed storage and fast self-evolution, Hopfield neural network is used to implement adaptive filtering algorithm LMS, so as to increase the computing speed. The model applied to sEMG signal denoising can achieve a better filtering effect.
Dongye Sun, Wen-Pei Sung and Ran Chen
J. H. Wang et al., "Wavelet-Based Neural Network Adaptive Filter for sEMG Denoising", Applied Mechanics and Materials, Vols. 121-126, pp. 4259-4264, 2012