## Documentation |

**Adaptive Neuro-Fuzzy Inference System**(ANFIS) A technique for automatically tuning Sugeno-type inference systems based on training data.

**aggregation**The combination of the consequents of each rule in a Mamdani fuzzy inference system in preparation for defuzzification.

**defuzzification**The process of transforming a fuzzy output of a fuzzy inference system into a crisp output.

**degree of membership**The output of a membership function, this value is always limited to between 0 and 1. Also known as a membership value or membership grade.

**firing strength**The degree to which the antecedent part of a fuzzy rule is satisfied. The firing strength may be the result of an AND or an OR operation, and it shapes the output function for the rule. Also known as

*degree of fulfillment*.**fuzzification**The process of generating membership values for a fuzzy variable using membership functions.

**fuzzy c-means clustering**A data clustering technique wherein each data point belongs to a cluster to a degree specified by a membership grade.

**fuzzy inference system (FIS)**The overall name for a system that uses fuzzy reasoning to map an input space to an output space.

**fuzzy singleton**A fuzzy set with a membership function that is unity at a one particular point and zero everywhere else.

**implication**The process of shaping the fuzzy set in the consequent based on the results of the antecedent in a Mamdani-type FIS.

**Mamdani-type inference****A type of fuzzy inference in which the fuzzy sets from the consequent of each rule are combined through the aggregation operator and the resulting fuzzy set is defuzzified to yield the output of the system.****membership function (MF)**A function that specifies the degree to which a given input belongs to a set or is related to a concept.

**singleton output function**An output function that is given by a spike at a single number rather than a continuous curve. In the Fuzzy Logic Toolbox™ software, it is only supported as part of a zero-order Sugeno model.

**subtractive clustering**A technique for automatically generating fuzzy inference systems by detecting clusters in input-output training data.

**Sugeno-type inference**A type of fuzzy inference in which the consequent of each rule is a linear combination of the inputs. The output is a weighted linear combination of the consequents.

Was this topic helpful?