Zobrazeno 1 - 10
of 225
pro vyhledávání: '"Babu, Prabhu"'
This work considers Maximum Likelihood Estimation (MLE) of a Toeplitz structured covariance matrix. In this regard, an equivalent reformulation of the MLE problem is introduced and two iterative algorithms are proposed for the optimization of the equ
Externí odkaz:
http://arxiv.org/abs/2307.03923
In this paper, we propose two new algorithms for maximum-likelihood estimation (MLE) of high dimensional sparse covariance matrices. Unlike most of the state of-the-art methods, which either use regularization techniques or penalize the likelihood to
Externí odkaz:
http://arxiv.org/abs/2305.06629
Autor:
Stoica, Petre, Babu, Prabhu
The Pearson-Matthews correlation coefficient (usually abbreviated MCC) is considered to be one of the most useful metrics for the performance of a binary classification or hypothesis testing method (for the sake of conciseness we will use the classif
Externí odkaz:
http://arxiv.org/abs/2305.05974
Autor:
Babu, Prabhu, Stoica, Petre
In this paper we propose a new iterative algorithm to solve the fair PCA (FPCA) problem. We start with the max-min fair PCA formulation originally proposed in [1] and derive a simple and efficient iterative algorithm which is based on the minorizatio
Externí odkaz:
http://arxiv.org/abs/2305.05963
Autor:
Stoica, Petre, Babu, Prabhu
Factor analysis (FA) or principal component analysis (PCA) models the covariance matrix of the observed data as R = SS' + {\Sigma}, where SS' is the low-rank covariance matrix of the factors (aka latent variables) and {\Sigma} is the diagonal matrix
Externí odkaz:
http://arxiv.org/abs/2304.08813
Autor:
Saini, Astha, Babu, Prabhu
In this comment, we present a simple alternate derivation to the IRW-FCM algorithm presented in "Iteratively Re-weighted Algorithm for Fuzzy c-Means" for Fuzzy c-Means problem. We show that the iterative steps derived for IRW-FCM algorithm are nothin
Externí odkaz:
http://arxiv.org/abs/2209.07715
This paper investigates the hybrid source localization problem using the four radio measurements - time of arrival (TOA), time difference of arrival (TDOA), received signal strength (RSS) and angle of arrival (AOA). First, after invoking tractable ap
Externí odkaz:
http://arxiv.org/abs/2205.03881
Source localization techniques incorporating hybrid measurements improve the reliability and accuracy of the location estimate. Given a set of hybrid sensors that can collect combined time of arrival (TOA), received signal strength (RSS) and angle of
Externí odkaz:
http://arxiv.org/abs/2204.06198
Dynamic target detection using FMCW waveform is challenging in the presence of interference for different radar applications. Degradation in SNR is irreparable and interference is difficult to mitigate in time and frequency domain. In this paper, a w
Externí odkaz:
http://arxiv.org/abs/2204.02236
In this letter, we propose an algorithm for learning a sparse weighted graph by estimating its adjacency matrix under the assumption that the observed signals vary smoothly over the nodes of the graph. The proposed algorithm is based on the principle
Externí odkaz:
http://arxiv.org/abs/2202.02815