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The fitting of a collection of noisy data points to a circle is a nonlinear and challenging problem, and it plays an important role in many signal processing applications. This paper proposes a semi-definite programming solution for the circle fitting problem based on the semi-definite relaxation technique. The relaxation of the maximum likelihood estimation converts a nonconvex problem to an approximate...
This letter considers the problem of simultaneously locating multiple disjoint sources and refining erroneous sensor positions using TDOA measurements. The previous work by Yang and Ho <citerefgrp><citeref refid="ref1"/> </citerefgrp> to solve this problem cannot provide optimum accuracy for the sensor positions. The proposed estimator improves the previous method so that...
The use of calibration emitters is known to be able to improve TDOA source localization accuracy when sensor positions are not accurate. This paper derives through CRLB analysis the conditions under which the sensor position errors can be completely eliminated in a source location estimate via deploying multiple calibration emitters whose positions can be erroneous. The implications on the geometric...
One nodus existing in Chinese word segmentation is the ambiguity problem of which more than 85% are crossing ambiguity, therefore it is significant to decrease the error in dealing with the crossing ambiguity. Taking the advantage of the characteristics of the crossing ambiguity string, a novel method based on the mutual information and t-test difference is proposed to deal with the ambiguities in...
The fitting of a number of noisy data points with a circle has found numerous applications in image processing and pattern recognition. This paper examines two methods to estimate the circle parameters: the Maximum Likelihood (ML) method and the Full-Least-Squares (FLS) method. The ML method is based on the noisy model from the data while the FLS method minimizes the geometric distance square. We...
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