Classification of musical intervals by spiking neural networks: Perfect student in solfége classes

被引：1
|
作者：
Bukh, A. V. [1 ]
Rybalova, E. V. [1 ]
Shepelev, I. A. [1 ,2 ]
Vadivasova, T. E. [1 ]
机构：
[1] Saratov NG Chernyshevskii State Univ, Inst Phys, 83 Astrakhanskaya St, Saratov 410012, Russia
[2] Almetyevsk State Petr Inst, 2 Lenin St, Almetyevsk 423462, Russia
来源：
CHAOS | 2024年 / 34卷 / 06期
基金：
俄罗斯科学基金会;
关键词：
TRANSMISSION; NEURONS; POWER; MODEL;
D O I：
10.1063/5.0210790
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
We investigate a spike activity of a network of excitable FitzHugh-Nagumo neurons, which is under constant two-frequency auditory signals. The neurons are supplemented with linear frequency filters and nonlinear input signal converters. We show that it is possible to configure the network to recognize a specific frequency ratio (musical interval) by selecting the parameters of the neurons, input filters, and coupling between neurons. A set of appropriately configured subnetworks with different topologies and coupling strengths can serve as a classifier for musical intervals. We have found that the selective properties of the classifier are due to the presence of a specific topology of coupling between the neurons of the network.
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页数：9
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