A New Spike Membership Function for the Recognition and Processing of Spatiotemporal Spike Patterns: Syllable-Based Speech Recognition Application

Abigail María Elena Ramírez-Mendoza, Wen Yu () and Xiaoou Li
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Abigail María Elena Ramírez-Mendoza: Department of Autonomous Air and Underwater Navigation Systems, French Mexican Laboratory of Informatics and Automatic Control, Mixed International Unit (LAFMIA UMI), Center for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV-IPN), National Council of Science and Technology (CONACYT), Av. Instituto Politécnico Nacional 2508, San Pedro Zacatenco, Mexico City CP 07360, Mexico
Wen Yu: Department of Automatic Control, CINVESTAV-IPN, Av. Instituto Politécnico Nacional 2508, San Pedro Zacatenco, Mexico City CP 07360, Mexico
Xiaoou Li: Computer Department, CINVESTAV-IPN, Av. Instituto Politécnico Nacional 2508, San Pedro Zacatenco, Mexico City CP 07360, Mexico

Mathematics, 2023, vol. 11, issue 11, 1-28

Abstract: This paper introduces a new spike activation function (SPKAF) or spike membership function for fuzzy adaptive neurons (FAN), developed for decoding spatiotemporal information with spikes, optimizing digital signal processing. A solution with the adaptive network-based fuzzy inference system (ANFIS) method is proposed and compared with that of the FAN-SPKAF model, obtaining very precise simulation results. Stability analysis of systems models is presented. An application to voice recognition using solfeggio syllables in Spanish is performed experimentally, comparing the methods of FAN-step activation function (STEPAF)-SPKAF, Augmented Spiking Neuron Model, and Augmented FAN-STEPAF-SPKAF, achieving very good results.

Keywords: fuzzy inference systems; fuzzy system models; neuro-fuzzy systems; learning; fuzzy adaptive neuron; membership function; activation function; spiking neuron; decoding; pattern recognition; syllable-based speech recognition (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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