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In this paper, a new classifier called minimax-probability based fuzzy hyper-ellipsoid machine (MP-FHM) is proposed. It offers an alternative implementation of the minimax probability based classification with hyper plane and can be taken as an extended version of the ball-model based classifier. By the theorem proposed by Marshall and Qlkin, the training procedure of MP-FHM can be transformed into...
Based on an integration of a simple impulse detector and a robust neuro-fuzzy (RNF) network, a new effective filter for color images corrupted by impulse noise is presented in this paper. There are two distinctive properties of the proposed method. The first is the use of a simple impulse detector. The other is the use of a novel membership function in the design of the adaptive RNF network, making...
This paper adopts a Bayesian approach to learn an optimal nonlinear classifier that is relevant to the classification task of semisupervised problems. The approach uses a prior weight to emphasize on the importance of class, which acts as a parameter of the likelihood function for both labeled and unlabeled data. We derive an expectation-maximization (EM) algorithm to compute maximum likelihood point...
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