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Neuro-Fuzzy Designer

Design, train, and test Sugeno-type fuzzy inference systems

Description

The Neuro-Fuzzy Designer app lets you design, train, and test adaptive neuro-fuzzy inference systems (ANFIS) using input/output training data.

Using this app, you can:

  • Tune membership function parameters of Sugeno-type fuzzy inference systems.

  • Automatically generate an initial inference system structure based on your training data.

  • Modify the inference system structure before tuning.

  • Prevent overfitting to the training data using additional checking data.

  • Test the generalization ability of your tuned system using testing data.

  • Export your tuned fuzzy inference system to the MATLAB® workspace.

You can use the Neuro-Fuzzy Designer to train a Sugeno-type fuzzy inference system that:

  • Has a single output.

  • Uses weighted average defuzzification.

  • Has output membership functions all of the same type, for example linear or constant.

  • Has complete rule coverage with no rule sharing; that is, the number of rules must match the number of output membership functions, and every rule must have a different consequent.

  • Has unity weight for each rule.

  • Does not use custom membership functions.

Open the Neuro-Fuzzy Designer App

  • MATLAB Toolstrip: On the Apps tab, under Control System Design and Analysis, click the app icon.

  • MATLAB command prompt: Enter neuroFuzzyDesigner.

Programmatic Use

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neuroFuzzyDesigner opens the Neuro-Fuzzy Designer app.

neuroFuzzyDesigner(fis) opens the app and loads the fuzzy inference system fis. fis can be any valid sugfis object in the MATLAB workspace.

You can create an initial Sugeno-type fuzzy inference system from training data using the genfis command.

neuroFuzzyDesigner(fileName) opens the app and loads a fuzzy inference system. fileName is the name of a .fis file on the MATLAB path.

To save a fuzzy inference system to a .fis file:

  • In the Fuzzy Logic Designer, select File > Export > To File

  • At the command line, use writeFIS.

Compatibility Considerations

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Not recommended starting in R2018b

Introduced in R2014b