Robust compressive sensing(CS) reconstruction has become an attractive research topic in recent years. Robust CS aims to reconstruct the sparse signals under non-Gaussian(i.e. heavy tailed) noises where traditional CS reconstruction algorithms may perform very poorly due to utilizing l2 norm of the residual vector in optimization. Most of existing robust CS reconstruction algorithms are based o...

Effective seizure detection from long-term EEG is highly important for seizure diagnosis. Existing methods usually design the feature and classifier individually, while little work has been done for the simultaneous optimization of the two parts. This work proposes a deep network to jointly learn a feature and a classifier so that they could help each other to make the whole system optimal. To ...

A soft parameter function penalized normalized maximum correntropy criterion (SPF-NMCC) algorithm is proposed for sparse system identification. The proposed SPF-NMCC algorithm is derived on the basis of the normalized adaptive filter theory, the maximum correntropy criterion (MCC) algorithm and zero-attracting techniques. A soft parameter function is incorporated into the cost function of the t...

This paper addresses the multi-sensor fusion target tracking problem based on maximum mixture correntropy in non-Gaussian noise environments exclusively using Doppler measurements. As measurements are non-linear, a statistical linear regression model is constructed unscented transformation. Then, centralized measurement developed, and determined, which contains high-order statistics of state pr...

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy THE CORRENTROPY MACE FILTER FOR IMAGE RECOGNITION By Kyu-Hwa Jeong August 2007 Chair: José C. Principe Major: Electrical and Computer Engineering The major goal of my research was to develop nonlinear methods of the family of distortion ...