Music recognition algorithm based on T-S cognitive neural network

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 weigh...

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Autor principal: Yan Fei
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Lenguaje:EN
Publicado: De Gruyter 2019
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t-s
Acceso en línea:https://doaj.org/article/b3d6a21b4d3347a98a9de43671b997bf
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spelling oai:doaj.org-article:b3d6a21b4d3347a98a9de43671b997bf2021-12-05T14:11:04ZMusic recognition algorithm based on T-S cognitive neural network2081-693610.1515/tnsci-2019-0023https://doaj.org/article/b3d6a21b4d3347a98a9de43671b997bf2019-04-01T00:00:00Zhttps://doi.org/10.1515/tnsci-2019-0023https://doaj.org/toc/2081-6936The 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.Yan FeiDe Gruyterarticlet-scognitive neural networkmusic recognitionNeurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENTranslational Neuroscience, Vol 10, Iss 1, Pp 135-140 (2019)
institution DOAJ
collection DOAJ
language EN
topic t-s
cognitive neural network
music recognition
Neurosciences. Biological psychiatry. Neuropsychiatry
RC321-571
spellingShingle t-s
cognitive neural network
music recognition
Neurosciences. Biological psychiatry. Neuropsychiatry
RC321-571
Yan Fei
Music recognition algorithm based on T-S cognitive neural network
description 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.
format article
author Yan Fei
author_facet Yan Fei
author_sort Yan Fei
title Music recognition algorithm based on T-S cognitive neural network
title_short Music recognition algorithm based on T-S cognitive neural network
title_full Music recognition algorithm based on T-S cognitive neural network
title_fullStr Music recognition algorithm based on T-S cognitive neural network
title_full_unstemmed Music recognition algorithm based on T-S cognitive neural network
title_sort music recognition algorithm based on t-s cognitive neural network
publisher De Gruyter
publishDate 2019
url https://doaj.org/article/b3d6a21b4d3347a98a9de43671b997bf
work_keys_str_mv AT yanfei musicrecognitionalgorithmbasedontscognitiveneuralnetwork
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