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“”“”This node represents two inferred fuzzy sets that are mirrors of one another.“”"
This node is a convenient extension to a Fuzzy Inference that allows the definition of two inferred fuzzy sets that have mirrored membership functions (and the union of the two mirrored sets as a combined fuzzy set). It takes up to three inputs - the truths for each fuzzy set that this node defines.
Typically, fuzzy inference is used to determine the truth (degree of membership) of a fuzzy set in a fuzzy logic network. As the name of the node suggests, the truth of the fuzzy set is inferred from the truths of each input (ie, while a Fuzzy Input is connected to crisp values, this node is connected to fuzzy values). The node has two outputs for each fuzzy set defined by the node: the truth of the fuzzy set inferred from the inputs (a float value that is used in subsequent fuzzy logic statements) and a FuzzySet struct that contains the discretized membership function, the truth value, and the crisp range associated with the fuzzy set. The struct is used for defuzzification.
The minimum of the crisp range associated with this fuzzy set.
The maximum of the crisp range associated with this fuzzy set.
Fuzzy Set Name
The name of the fuzzy set. Each name for a fuzzy set should be unique for a given fuzzy variable.
Mirrored Fuzzy Set Name
The name of the mirrored fuzzy set.
Combined Fuzzy Set Name
THe name of the combined fuzzy set (the original membership function and the mirrored membership function combined).
Common membership function presets for the fuzzy set defined on the node. The control points for each preset can be adjusted by the user.
Reverses the positions of the control points for the current preset.
A visualization of the membership function used to determine the degree of membership in the membership set. If the preset is set to “Custom” the ramp parameter becomes editable. Additional visualization ramps “Membership Mirrored” and “Membership Combined” are displayed if “Mirrored” and “Combine Mirror” are toggled respectively.
Toggles a mirrored fuzzy set for the fuzzy set defined by the node. If this is toggled, outputs will be added to the node for the mirrored fuzzy set.
Toggles a combined fuzzy set that has a membership function that is a combination of the mirrored fuzzy set and the original fuzzy set. If this is toggled (and a “Mirrored” is also toggled, outputs will be added to the node for the combined fuzzy set.
Number of Samples
The number of samples to sample the membership function at when determining the degree of membership. The larger the value, the more accurate the representation of the fuzzy set will be.
Specifies the interpolation to use between the control points in the membership function.
The range parameter is the range of the membership values defined by the membership function (must be between 0 and 1), and is interpreted differently for each preset. For example, for the “Triangle” preset, the minimum will define the value “Position 1” and “Position 3,” and the maximum will define the value for “Position 2.”
The positions of each control point used to adjust each preset membership function. The position is a value between 0 and 1, and “Position 4” > “Position 3” > “Position 2” > “Position 1” (the positions will automatically be adjusted such that this remains true).
The inferred truth value for the fuzzy set defined by this node (corresponds to “Membership Function”).
Fuzzy Value Mirrored
The inferred truth value for the mirrored set defined by this node (corresponds to “Membership Function Mirrored”).
Fuzzy Value Combined
The inferred truth value for the combined set defined by this node (corresponds to “Membership Function Combined”).
The fuzzy value inferred from the input fuzzy values.
A struct that contains the discretized membership function, the fuzzy value, and the range that the fuzzy set is defined over.