Search Results for author: Prabhu Babu

Found 14 papers, 1 papers with code

Comments on "Iteratively Re-weighted Algorithm for Fuzzy c-Means"

no code implementations16 Sep 2022 Astha Saini, Prabhu Babu

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.

Majorization-Minimization based Hybrid Localization Method for High Precision Localization in Wireless Sensor Networks

no code implementations8 May 2022 Kuntal Panwar, Prabhu Babu, R. Jyothi

The resultant weighted least-squares problem obtained, which is non-smooth and non-convex, is solved using the principle of the majorization-minimization (MM), leading to an iterative algorithm that has a guaranteed convergence.

Optimal Sensor Placement for Hybrid Source Localization Using Fused TOA-RSS-AOA Measurements

no code implementations13 Apr 2022 Kuntal Panwar, Ghania Fatima, Prabhu Babu

In this paper, we present an optimal sensor placement methodology, which is based on the principle of majorization-minimization (MM), for hybrid localization technique.

Learning Sparse Graphs via Majorization-Minimization for Smooth Node Signals

no code implementations6 Feb 2022 Ghania Fatima, Aakash Arora, Prabhu Babu, Petre Stoica

The proposed algorithm does not require tuning of any hyperparameter and it has the desirable feature of eliminating the inactive variables in the course of the iterations - which can help speeding up the algorithm.

Graph Learning

PDMM: A novel Primal-Dual Majorization-Minimization algorithm for Poisson Phase-Retrieval problem

no code implementations16 Oct 2021 Ghania Fatima, Zongyu Li, Aakash Arora, Prabhu Babu

In this paper, we introduce a novel iterative algorithm for the problem of phase-retrieval where the measurements consist of only the magnitude of linear function of the unknown signal, and the noise in the measurements follow Poisson distribution.


Optimal Sensor Placement for Source Localization: A Unified ADMM Approach

no code implementations8 Sep 2021 Nitesh Sahu, Linlong Wu, Prabhu Babu, Bhavani Shankar M. R., Björn Ottersten

Source localization plays a key role in many applications including radar, wireless and underwater communications.

UNIPOL: Unimodular sequence design via a separable iterative quartic polynomial optimization for active sensing systems

no code implementations9 Jul 2021 Surya Prakash Sankuru, Prabhu Babu, Mohammad Alaee-Kerahroodi

Sequences having better autocorrelation properties play a crucial role in enhancing the performance of active sensing systems.

Design of MIMO Radar Waveforms based on lp-Norm Criteria

no code implementations7 Apr 2021 Ehsan Raei, Mohammad Alaee-Kerahroodi, Prabhu Babu, M. R. Bhavani Shankar

Multiple-input multiple-output (MIMO) radars transmit a set of sequences that exhibit small cross-correlation sidelobes, to enhance sensing performance by separating them at the matched filter outputs.

Designing sequence set with minimal peak side-lobe level for applications in high resolution RADAR imaging

no code implementations7 Sep 2020 Surya Prakash Sankuru, R Jyothi, Prabhu Babu, Mohammad Alaee-Kerahroodi

Constant modulus sequence set with low peak side-lobe level is a necessity for enhancing the performance of modern active sensing systems like Multiple Input Multiple Output (MIMO) RADARs.

A Fast Iterative Algorithm to design phase only sequences by minimizing the ISL metric

no code implementations15 Jul 2020 Surya Prakash Sankuru, Prabhu Babu

Unimodular/Phase only sequence having impulse like aperiodic auto-correlation function plays a central role in the applications of RADAR, SONAR, Cryptography, and Wireless (CDMA) Communication Systems.

Orthogonal Sparse PCA and Covariance Estimation via Procrustes Reformulation

no code implementations12 Feb 2016 Konstantinos Benidis, Ying Sun, Prabhu Babu, Daniel P. Palomar

In addition, we propose a method to improve the covariance estimation problem when its underlying eigenvectors are known to be sparse.

Robust Estimation of Structured Covariance Matrix for Heavy-Tailed Elliptical Distributions

no code implementations17 Jun 2015 Ying Sun, Prabhu Babu, Daniel P. Palomar

This paper considers the problem of robustly estimating a structured covariance matrix with an elliptical underlying distribution with known mean.

Sparse Generalized Eigenvalue Problem via Smooth Optimization

1 code implementation28 Aug 2014 Junxiao Song, Prabhu Babu, Daniel P. Palomar

Then an algorithm is developed via iteratively majorizing the surrogate function by a quadratic separable function, which at each iteration reduces to a regular generalized eigenvalue problem.

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