Fully adaptive neural nonlinear FIR filters
Tóm tắt
A class of algorithms for training neural adaptive filters employed for nonlinear adaptive filtering is introduced. Sign algorithms incorporated with the fully adaptive normalised nonlinear gradient descent (SFANNGD) algorithm, normalised nonlinear gradient descent (SNNGD) algorithm and nonlinear gradient descent (SNGD) algorithm are proposed. The SFANNGD, SNNGD and the SNGD are derived based upon the principle of the sign algorithm used in the least mean square (LMS) filters. Experiments on nonlinear signals confirm that SFANNGD, SNNGD and the SNGD algorithms perform on par as compared to their basic algorithms but the sign algorithm decreases the overall computational complexity of the adaptive filter algorithms.
Từ khóa
#Finite impulse response filter #Adaptive filters #Computational complexity #Mathematical model #Cost function #Convergence #Taylor series #Educational institutions #Information systems #Filtering algorithmsTài liệu tham khảo
moreira, 1995, Neural Networks with Adaptive Learning Rate and Momentum Terms, Tech Rep IDIAP, 4
10.1109/78.774769
10.1109/97.969448
10.1049/el:20000631
10.1109/ICASSP.1995.480502
10.1109/18.256503
10.1002/047084535X
10.1109/72.80202
haykin, 1999, Neural Networks A Comprehensive Foundation