Wenli Jiang

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Analyzed here is the physical interpretation of objective function of semi-supervised fuzzy C-means (SS-FCM) algorithm and its coefficient alpha. A conclusion-Stutzpsilas modification to the objective function of Pedrycz is much clearer: unlabeled samples involves in unsupervised learning of FCM, labeled samples involves in unsupervised learning with(More)
Source localization accuracy is very sensitive to sensor location error. This paper performs analysis and develops a solution for locating a moving source using time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements with the use of a calibration emitter. Using a Gaussian random signal model, we first derive the Cramér-Rao(More)
—This paper describes a sparse imaging approach for estimating change images from a constellation of multistatic radar. In our setup, radar antennas are arranged around the perimeter of a surveillance region. This provides large angular diversity but a very small angular sampling. Conventional backprojection imaging techniques applied to this data produce(More)
A single satellite to satellite passive tracking from angles measurements have great significance in space surveillance system. This paper focuses on the state observability problem, which is the important theory issue for satellite to satellite passive tracking. The state motion equation and measurement equation are deduced in three-dimensional modified(More)
Dependency between business and resources that ensure the normal function of the business has increased dramatically in size and complexity. As communication network becomes larger and more complex, the need for advanced correlation between audit alarm and business is becoming urgent. This paper proposes a framework for business-oriented security audit,(More)
The paper considers the problem of jointly reconstructing multiple block-sparse signals with block partition unknown. Based on the framework of block sparse Bayesian learning (BSBL), we develop a new multitask recovery algorithm, called the extension algorithm of multitask block sparse Bayesian learning (EMBSBL). In contrast to existing methods, EMBSBL(More)