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Microarrays have been useful in the diagnosis and treatment due to their abilities to survey a large number of genes quickly and to study samples with small amount. With the development of microarray technology, the prospects for effective and reliable disease diagnosis and management can be significantly improved if the classification performance on(More)
A shared-weight neural network based on mathematical morphology is introduced. The feature extraction process is learned by interaction with the classification process. Feature extraction is performed using gray-scale hit-miss transforms that are independent of gray-level shifts. The morphological shared-weight neural network (MSNN) is applied to automatic(More)
Recently, a novel learning algorithm called extreme learning machine (ELM) was proposed for efficiently training single-hidden-layer feedforward neural networks (SLFNs). It was much faster than the traditional gradient-descent-based learning algorithms due to the analytical determination of output weights with the random choice of input weights and hidden(More)
DNA microarray is a multiplex technology used in molecular biology and biomedicine. It consists of an arrayed series of thousands of microscopic spots of DNA oligonucleotides, called features, of which the result should be analyzed by computational methods. Analyzing microarray data using intelligent computing methods has attracted many researchers in(More)