Deep neuro-fuzzy architectures

Anuar Dorzhigulov; Alex James Pappachen

doi:10.1007/978-3-030-14524-8_15

Deep neuro-fuzzy architectures

Anuar Dorzhigulov, Alex James Pappachen

Department of Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Fuzzy logic inspires from the non-deterministic behaviour of human brain computations. The fusion of neural networks and fuzzy logic such as neuro-fuzzy architectures is natural, as both represent elementary inspiration from brain computations involving learning, adaptation and ability to tolerate noise. This chapter focuses on neuro-fuzzy and alike solutions for machine learning from perspective of functionality, architectures and applications.

Original language	English
Title of host publication	Modeling and Optimization in Science and Technologies
Publisher	Springer Verlag
Pages	195-213
Number of pages	19
DOIs	https://doi.org/10.1007/978-3-030-14524-8_15
Publication status	Published - Jan 1 2020

Publication series

Name	Modeling and Optimization in Science and Technologies
Volume	14
ISSN (Print)	2196-7326
ISSN (Electronic)	2196-7334

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ASJC Scopus subject areas

Modelling and Simulation
Medical Assisting and Transcription
Applied Mathematics

Cite this

Dorzhigulov, A., & James Pappachen, A. (2020). Deep neuro-fuzzy architectures. In Modeling and Optimization in Science and Technologies (pp. 195-213). (Modeling and Optimization in Science and Technologies; Vol. 14). Springer Verlag. https://doi.org/10.1007/978-3-030-14524-8_15

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Access to Document

10.1007/978-3-030-14524-8_15