Noise Effects in Fuzzy Modelling Systems

09/30/2000
by   P. J. Costa Branco, et al.
0

Noise is source of ambiguity for fuzzy systems. Although being an important aspect, the effects of noise in fuzzy modeling have been little investigated. This paper presents a set of tests using three well-known fuzzy modeling algorithms. These evaluate perturbations in the extracted rule-bases caused by noise polluting the learning data, and the corresponding deformations in each learned functional relation. We present results to show: 1) how these fuzzy modeling systems deal with noise; 2) how the established fuzzy model structure influences noise sensitivity of each algorithm; and 3) whose characteristics of the learning algorithms are relevant to noise attenuation.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/11/2012

A Study on Fuzzy Systems

We use princiles of fuzzy logic to develop a general model representing ...
research
05/21/2014

Robust Fuzzy corner detector

Reliable corner detection is an important task in determining the shape ...
research
11/22/2020

Random noise attenuation on finite-difference wave propagation using fuzzy transform

Fuzzy Transform (F-transform) has been introduced as an approximation me...
research
01/17/2017

Multiobjective Optimization of Solar Powered Irrigation System with Fuzzy Type-2 Noise Modelling

Optimization is becoming a crucial element in industrial applications in...
research
03/29/2017

Marginal likelihood based model comparison in Fuzzy Bayesian Learning

In a recent paper [1] we introduced the Fuzzy Bayesian Learning (FBL) pa...
research
02/03/2020

Improving the Evaluation of Generative Models with Fuzzy Logic

Objective and interpretable metrics to evaluate current artificial intel...
research
01/13/2015

An Adaptive Neuro-Fuzzy Inference System Modeling for Grid-Adaptive Interpolation over Depth Images

A suitable interpolation method is essential to keep the noise level min...

Please sign up or login with your details

Forgot password? Click here to reset