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In this paper, a new perturbation analysis algorithm for the MUltiple SIgnal Classification (MUSIC) estimator applied to a Hermitian Toeplitz covariance matrix is presented. Inspired by the perspective that the MUSIC algorithm can be recognized as a structured matrix approximation, the perturbation of parameter estimates can be predicted more accurately by seeking the minimum of a Frobenius norm....
Relevance vector machine (RVM) is one kind of intelligent classification algorithm with good performance. However, it is difficult to classify targets which have similar characteristics using RVM. In this paper a sort of dynamic classification algorithm which combines RVM and Particle filtering (PF) is proposed: When the characteristics of targets are resembling at initial state, this algorithm can...
The proper extraction of road seeds is the premier step of road network extraction from high resolution remote sensing images. An optimal road seed extraction algorithm is proposed. Firstly, Canny-Deriche edge detection and spatial FCM (fuzzy c means) region extraction are performed separately to detect the details.Secondly, an averaged Hausdorff distance is introduced to evaluate the difference between...
We study the problem of learning to rank images for image retrieval. For a noisy set of images indexed or tagged by the same keyword, we learn a ranking model from some training examples and then use the learned model to rank new images. Unlike previous work on image retrieval, which usually coarsely divide the images into relevant and irrelevant images and learn a binary classifier, we learn the...
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