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This paper presents a first order Takagi-Sugeno-Kang (TSK) type fuzzy equalizer to mitigate nonlinear power amplifier distortion effects from the received signal in orthogonal frequency division multiplexing (OFDM) systems. Here we propose a Comprehensive Learning Particle Swarm Optimizer (CLPSO) based structure identification of the TSK equalizer. CLPSO uses a new learning strategy that achieves...
In this paper, we present the problem of appropriate feature selection for constructing a Maximum Entropy (ME) based Named Entity Recognition (NER) system under the multiobjective optimization (MOO) framework. Two conflicting objective functions are simultaneously optimized using the search capability of MOO. These objectives are (i). the dimensionality of features, which is tried to be minimized,...
Prognostics has taken center stage in condition based maintenance (CBM) where it is desired to estimate remaining useful life (RUL) of a system so that remedial measures may be taken in advance to avoid catastrophic events or unwanted downtimes. Validation of such predictions is an important but difficult proposition and a lack of appropriate evaluation methods renders prognostics meaningless. Evaluation...
In this paper, a new line symmetry based classifier (LSC) is proposed to deal with pattern classification problems. In order to measure total amount of line symmetry of a particular point in a class, a new definition of line symmetry based distance is also proposed in this paper. The proposed line symmetry based classifier (LSC) utilizes this new definition of line symmetry distance for classifying...
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