Gaussian MF

Gaussian membership function

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Libraries:
Fuzzy Logic Toolbox / Membership Functions

Description

The Gaussian MF block implements a membership function based on a symmetric Gaussian function.

$$f\left(x;\sigma ,c\right)=e^{\frac{-{\left(x-c\right)}^2}{2{\sigma }^2}}$$

Here, c is the mean and σ is the standard deviation of the Gaussian function.

A Gaussian membership function is not the same as a Gaussian probability distribution. For example, a Gaussian membership function always has a maximum value of 1. For more information on Gaussian probability distributions, see Normal Distribution (Statistics and Machine Learning Toolbox).

Ports

Input

x — Input value

scalar | vector

Input value for which to compute membership values, specified as a scalar or vector.

Output

MF — Membership value

scalar | vector

Membership value, returned as a scalar or a vector. The dimensions of MF match the dimensions of x. Each element of MF is the membership value computed for the corresponding element of x.

Parameters

Standard deviation sigma — Standard deviation

1 (default) | scalar

Standard deviation σ of the Gaussian function.

Programmatic Use

Block Parameter: sigma

Type: string, character vector

Default: "1"

Mean c — Mean

0 (default) | scalar

Mean c of the Gaussian function.

Programmatic Use

Block Parameter: mu

Type: string, character vector

Default: "0"

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using Simulink® Coder™.

PLC Code Generation
Generate Structured Text code using Simulink® PLC Coder™.

Version History

Introduced before R2006a