Adaptive Neuro-Fuzzy Inference Systems (ANFIS) Library for Simulink

This Simulink library contains six ANFIS/CANFIS system variations.
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Aggiornato 1 mag 2015

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This library is for those who want to use the ANFIS/CANFIS system in the Simulink environment. Each model is implemented for training and operation in a sample-by-sample, on-line mode. For details see the included release notes. The main reference used to develop all the ANFIS/CANFIS models is:
Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence, Jyh-Shing Roger Jang, Chuen-Tsai Sun, Eiji Mizutani. Prentice Hall, Sept. 1997.

Cita come

Ilias Konsoulas (2024). Adaptive Neuro-Fuzzy Inference Systems (ANFIS) Library for Simulink (, MATLAB Central File Exchange. Recuperato .

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Creato con R2011b
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Versione Pubblicato Note della release

Killed some redundant variables and commands in s-function scripts. Added some new comments. Also introduced use of "if any(logical_condition)" loops instead of "if ~isempty(logical_condition) which should be a bit faster.

Improved S-function syntax. Also killed a small bug. Updated library should run a bit faster.

Fixed a bug in anfisim_scatter.m that prevented run with a single input. All models were tested for single input run successfully.

Introduced the method of gradient consistency checking. This assures the correctness of your backprop implementation. I also provided .m scripts that perform gradient checking to all (C)ANFIS functions of this library.

In the latest version of the users guide, I have included a new section describing how to make the demos runnable on your computer and briefly outlining what each demo is about.

OK, I corrected the name of the library file from NFA.mdl to NFA_matlab.mdl in order to make demos runnable.

Minor code changes, better comments and NFA User Guide corrections.

I have updated only the following form entries: a)Description, b)Tags c) Acknowledgement of other submissions.