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A new idea 'clone selection programming (CSP)' is introduced in this paper. The proposed methodology is used for deriving new algorithms in the area of evolutionary computing aimed at solving a wide range of problems. In CSP, antibodies represent candidate solutions, which are encoded according to the structure of antibody. The antibodies are able to keep(More)
A clonal selection programming (CSP)-based fault detection system is developed for performing induction machine fault detection and analysis. Four feature vectors are extracted from power spectra of machine vibration signals. The extracted features are inputs of an CSP-based classifier for fault identification and classification. In this paper, the proposed(More)
Microarray gene expression data usually consist of a large amount of genes. Among these genes, only a small fraction is informative for performing cancer diagnostic tests. This paper focuses on effective identification of informative genes. A newly developed gene selection criterion using the concept of Bayesian discriminant is used. The criterion measures(More)
In this paper, a new algorithm for lip tracking is proposed, fusing the strength of stochastic tracker and deterministic tracker. Particle filter and active shape models (ASM) are used as deterministic tracker and stochastic tracker respectively. In order not to build complex dynamic model, we use deterministic tracker instead of stochastic tracker to(More)
This paper focuses on enhancing the effectiveness of filter feature selection models from two aspects. First, feature-searching engine is modified based on optimization theory. Second, a point injection strategy is designed to improve the regularization capability of feature selection. The second topic is important, because overfitting is usually(More)