Structured Covariance Matrix Estimation for Noise-Type Radars

Estimation of Covariance Matrix in Signal Processing When the Noise Covariance Matrix is Arbitrary

Estimation of Covariance Matrix

Estimation of population covariance matrices from samples of multivariate data is important. (1) Estimation of principle components and eigenvalues. (2) Construction of linear discriminant functions. (3) Establishing independence and conditional independence. (4) Setting confidence intervals on linear functions. Suppose we observed p dimensional multivariate samples X1, X2, · · · , Xn i.i.d. wi...

Adaptive Thresholding for Sparse Covariance Matrix Estimation

In this article we consider estimation of sparse covariance matrices and propose a thresholding procedure that is adaptive to the variability of individual entries. The estimators are fully data-driven and demonstrate excellent performance both theoretically and numerically. It is shown that the estimators adaptively achieve the optimal rate of convergence over a large class of sparse covarianc...

Covariance Matrix Estimation for Reinforcement Learning

One of the goals in scaling reinforcement learning (RL) pertains to dealing with high-dimensional and continuous stateaction spaces. In order to tackle this problem, recent efforts have focused on harnessing well-developed methodologies from statistical learning, estimation theory and empirical inference. A key related challenge is tuning the many parameters and efficiently addressing numerical...

Covariance Matrix Estimation for Radar Applications

Acknowledgment I thank Selex ES and SESM for supporting my PhD's scholarship. Also, I express my gratitude to Dr. Alfonso Farina for his technical support during my research activities, the continuous assistance, encouragement and kindness demonstrated during these three years.