Neo-Fuzzy Neural Network for modeling of MIMO dynamics

Margarita Terziyska, Yancho Todorov, Lyubka Doukovska

Research output: Contribution to journalArticleScientificpeer-review


This paper presents the structure and the learning algorithm of a multi-input
multi-output (MIMO) Neo-fuzzy neural network for nonlinear system modeling. The applied approach lies on the idea of Neo-fuzzy neuron whose dynamics depend on its own temporal behavior, while his output is generated as a singleton function. To demonstrate efficiency of the proposed modeling structure, a simulation experiments in Matlab environment modeling a nonlinear MIMO process dynamics are performed.
Original languageEnglish
Pages (from-to)65
Number of pages70
JournalJournal of the Technical University – Sofia. Plovdiv branch, Bulgaria. Fundamental Sciences and Applications
Issue numberbook 1
Publication statusPublished - 2015
MoE publication typeA1 Journal article-refereed


  • control systems
  • optimization
  • modeling
  • artificial intelligence
  • Neural networks

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