Titlebook: Intelligent Computing in Signal Processing and Pattern Recognition; International Confer De-Shuang Huang,Kang Li,George William Irwin Book

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An Extended Learning Vector Quantization Algorithm Aiming at Recognition-Based Character Segmentatioegies is to design a classifier that can provide accurate rejection information. Many learning algorithms, such as GLVQ and H2M-LVQ, are not suitable for large category sets and multiple prototypes. More seriously, they often suffer from local minimum state and overtraining. In this paper, we propos

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Improved Decision Tree Algorithm: ID3+ogate value, our method overcomes some ID3’s disadvantages, such as preference bias and the inability to deal with unknown attribute values. The experimental results show that our method can competitively and efficiently solve the two problems. The first problems often leads to inferior decision tre

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Application of Support Vector Machines with Binary Tree Architecture to Advanced Radar Emitter Signa criterion. For computational efficiency, the multiclass support vector machines (SVMs) with binary tree architecture is introduced to recognize advanced RESs. Resemblance coefficient is used to convert multi-class problems into binary-class problems and consequently the structure of multi-class SVM

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Automatic Target Recognition in High Resolution SAR Image Based on Electromagnetic Characteristicsoss section (RCS) of complex military targets is calculated and high resolution inversed SAR (ISAR) image is simulated. The method of affine transform is used to extract the invariant features of the image contour of several types of airplanes. The image contours of several airplanes are real-time a

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Boosting in Random Subspace for Face Recognitionrandom subspace, is employed to improve generalization capability of boosting. Meanwhile the space complexity of training is lowered, and the classifier combination strategy can be used to further improve recognition accuracy. Using the method, we achieved 98.99% rank-1 recognition rate on FERET . p

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