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What is Membership Function (MF)

Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition, Analysis, and Image Processing
The membership function is a graphical representation of the magnitude of participation of each input. It associates weighting with each of the inputs that are processed.
Published in Chapter:
Biometric Identification System Using Neuro and Fuzzy Computational Approaches
Tripti Rani Borah (Gauhati University, India), Kandarpa Kumar Sarma (Gauhati University, India), and Pranhari Talukdar (Gauhati University, India)
DOI: 10.4018/978-1-4666-8654-0.ch016
Abstract
In all authentication systems, biometric samples are regarded to be the most reliable one. Biometric samples like fingerprint, retina etc. is unique. Most commonly available biometric system prefers these samples as reliable inputs. In a biometric authentication system, the design of decision support system is critical and it determines success or failure. Here, we propose such a system based on neuro and fuzzy system. Neuro systems formulated using Artificial Neural Network learn from numeric data while fuzzy based approaches can track finite variations in the environment. Thus NFS systems formed using ANN and fuzzy system demonstrate adaptive, numeric and qualitative processing based learning. These attributes have motivated the formulation of an adaptive neuro fuzzy inference system which is used as a DSS of a biometric authenticable system. The experimental results show that the system is reliable and can be considered to be a part of an actual design.
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More Results
Introduction to Fuzzy Logic and Fuzzy Linear Programming
An MF is a curve that defines how each point in the input space is mapped to a membership value (or degree of membership) between 0 and 1.
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Adaptive Neuro-Fuzzy Inference System in Agriculture
MF signifies the degree to which each input feature is mapped to a membership value between 0 and 1. It is basically a curve.
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Computing with Words Model for Emotion Recognition Using Interval Type-2 Fuzzy Sets
A membership function denotes the degree of belonging of an object into a particular attribute or set. For crisp sets, the MF is restricted to 0 or 1.On the other hand, fuzzy sets have MF within the interval [0, 1].
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