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The direct path interference (DPI) and multipath interference (MPI) cancellation is a key issue in non-cooperative passive radar. Existing cancellation methods always impose that restrain surplus large, such as least mean square (LMS), batch extensive cancellation algorithm (ECA-B) and computing expensive, such as spatial algorithm and extensive cancellation algorithm (ECA), which is impossible for...
Rail transit plays an increasingly important role in the public transportation system, and effectively reducing its headway is of great practical significance. An optimization method is proposed to minimize headway of mainline in moving block by comprehensively considering trip time. A particle swarm optimization (PSO) algorithm is developed to search for optimized points and value of speed limit...
In order to determine the parameters of belief-rule-base (BRB) accurately, several optimization methods have been proposed for training BRB, on the basis of a generic rule-base inference methodology using the evidential reasoning (RIMER) approach. These optimization methods are implemented offline, and such are not suitable for training BRB in a dynamic fashion. In this paper, two recursive algorithms...
This paper presents a fast stereo algorithm for obtaining disparity maps efficiently. We use a 3D model for storing and computing the depth map. The initial matching by intensity similarity is very fast by using the computational optimization. At the improving matching reliability step, two assumptions that were originally proposed by Marr and Poggio are adopted: uniqueness and continuity. It means...
Feature extraction (FE) methods have been proved to be very effective for dimension reduction, but the features attained are meaningless. In order to exploit the effectiveness of FE methods to support feature selection (FS), this paper proposed a new FS approach for clustering based on principal component analysis (PCA) called PS. It first uses PCA to transform the data from original feature space...
Feature selection is an important task in machine learning, pattern recognition and data mining. This paper proposed a new feature selection method for classification, named SD, which is based on scatter matrix used in linear discriminant analysis. The main feature of SD is its simplicity and independency of learning algorithms. High-dimensional data samples are first projected into a lower dimensional...
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