SFMI

PURPOSE

SYNOPSIS

DESCRIPTION

 SFMI M-file for SFMI.fig
      SFMI, by itself, creates a new SFMI or raises the existing
      singleton*.

      H = SFMI returns the handle to a new SFMI or the handle to
      the existing singleton*.

      SFMI('CALLBACK',hObject,eventData,handles,...) calls the local
      function named CALLBACK in SFMI.M with the given input arguments.

      SFMI('Property','Value',...) creates a new SFMI or raises the
      existing singleton*.  Starting from the left, property value pairs are
      applied to the GUI before SFMI_OpeningFunction gets called.  An
      unrecognized property name or invalid value makes property application
      stop.  All inputs are passed to SFMI_OpeningFcn via varargin.

      *See GUI Options on GUIDE's Tools menu.  Choose "GUI allows only one
      instance to run (singleton)".

 See also: GUIDE, GUIDATA, GUIHANDLES

CROSS-REFERENCE INFORMATION

• About ABOUT M-file for About.fig
• ApproxInputTrapezoids Approximate the membership functions by trapezoids forming a Ruspini-like partition
• ClusteringPreferences CLUSTERINGPREFERENCES M-file for ClusteringPreferences.fig
• CreateSystemWith2Rules Create a raw fuzzy system containing only two rules.
• DefaultClusteringOptions options - column vector containing parameters of the FCM clustering
• DefaultTuningOptions Create a vector containing the default values for tuning preferences
• DefaultTwoRulesOptions Create a column vector containing the default values for the options
• GetRawFISName GETRAWFISNAME M-file for GetRawFISName.fig
• GetRule Determine the rules for the current output fuzzy set
• GetTuningPreferences Determine the tuning options using a dialog box.
• InputClustering1D Perform Fuzzy C-Mean Clustering in each indata dimension separately
• MergeIdenticalClusters Merge antecedent clusters whose centers are identical
• MergeInputPartitions Genereate a common input partition in each input dimension by merging the
• MergePartRulebases Genereate a common rule base by merging the
• MergeSimilarSets Merge fuzzy sets whose params does not differ more than
• OutputClustering1D Perform Fuzzy C-Mean Clustering in each output dimension separately (1D clusterings)
• OutputDimensionSelect OUTPUTDIMENSIONSELECT M-file for OutputDimensionSelect.fig
• PlotPartition Display the clusters in the current dimension
• RBE_DSS Fuzzy system tuning with RBE-DSS
• RBE_SI Fuzzy system tuning by a varianat of the gradiant descent method and
• RoundFisData
• ShowClusteringPreferences Show the options of the clustering in the editbox in the main window
• ShowTuningPreferences Show the options of the system tuning in the editbox in the main window
• ShowTwoRulesPreferences Show the options (preferences) applied by the fuzzy system generation based on extreme
• Simplex Fuzzy system tuning with the Simplex method
• SortMfs Sort the membership functions in each dimension in ascending order.
• SystemSelect SYSTEMSELECT M-file for SystemSelect.fig
• SystemTuning1 Fuzzy system tuning with ACP + breakpoints as parameters
• SystemTuning2 Fuzzy system tuning with ACP + relative distances as parameters
• SystemTuning3 Fuzzy system tuning with ACP + Conserving Ruspini partition
• TwoRulesPreferences TWORULESPREFERENCES M-file for TwoRulesPreferences.fig