- Turkish Journal of Electrical Engineering and Computer Science
- Vol: 24 Issue: 5
- A new step-size searching algorithm based on fuzzy logic and neural networks for LMS adaptive beamfo...
A new step-size searching algorithm based on fuzzy logic and neural networks for LMS adaptive beamforming systems
Authors : Walter Orozco-tupacyupanqui, Mariko Nakano-miyatake, Hector Perez Meana
Pages : 4322-4338
View : 9 | Download : 6
Publication Date : 9999-12-31
Article Type : Makaleler
Abstract :In this paper, a novel algorithm based on fuzzy logic and neural networks is proposed to find an approximation of the optimal step size $\mu $ for least-mean-squares (LMS) adaptive beamforming systems. A new error ensemble learning (EEL) curve is generated based on the final prediction value of the ensemble-average learning curve of the LMS adaptive algorithm. This information is classified and fed into a back propagation neural network, which automatically generates membership functions for a fuzzy inference system. An estimate of the optimal step size is obtained using a group of linguistic rules and the corresponding defuzzification method. Computer simulations show that a useful approximation of the optimal step size is obtained under different signal-to-noise plus interference ratios. The results are also compared with data obtained from a statistical analysis performed on the EEL curve. As a result of this application, a better mean-square-error is observed during the training process of the adaptive array beamforming system, and a higher directivity is achieved in the radiation beam patterns.Keywords : Adaptive filtering, adaptive beamforming, neural-fuzzy systems, least-mean-square algorithm, membership functions