Now showing items 1-4 of 4
Support vector regression for surveillance purposes
(SPRINGER-VERLAG BERLIN, 2006)
This paper addresses the problem of applying powerful statistical pattern classification algorithm based on kernel functions to target tracking on surveillance systems. Rather than directly adapting a recognizer we develop ...
Unconditional maximum likelihood approach for localization of near-field sources in 3-D space
Since maximum likelihood (ML) approaches have better resolution performance than the conventional localization methods in the presence of less number and highly correlated source signal samples and low signal to noise ...
Near field parameter estimation of moving sources with recursive expectation maximization algorithm
In this paper maximum likelihood (ML) estimator is proposed for the joint estimation of the direction of arrival (DOA) and range parameters of moving sources in the near-field of the antenna array. ML estimation algorithm ...
Support vector machines based target tracking techniques
This paper addresses the problem of aplying powerful statistical pattern classification algorithms based on kernels to target tracking. Rather than directly adapting a recognizer we develop a localizer directly using the ...