Affiliation:
1. School of Music, Jiaozuo Teachers College , Jiaozuo , Henan 454000 , China
Abstract
Abstract
The main task of music recognition is to acquire relevant information of music content through processing and feature extraction of audio signals, and then used for comparison, classification, and automatic recording. The cognitive neural network based on T-S model is used to train the network weights with improved genetic algorithm in the paper. The strategy of membership function parameter adjustment is combined with the combination of momentum method and learning rate adaptive adjustment. The new proposed algorithm can be used in the music recognition algorithm by adding a compensation factor related to the input dimension on the membership degree, and the experimental result of the rule disaster caused by the excessive input dimension shows that the new proposed method can be applied to the music recognition system. At the same time, it shows that the accuracy rate of the recognition network is more accurate than that of the other algorithms, and its robustness is better.
Cited by
10 articles.
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