Consensus-based Distributed Total Least-squares Estimation Using Parametric Semidefinite Programming

We propose a new distributed algorithm to solve the total least-squares (TLS) problem when data are distributed over a multi-agent network. To develop the proposed algorithm, named distributed ADMM TLS (DA-TLS), we reformulate the TLS problem as a parametric semidefinite program and solve it using t...

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Bibliographic Details
Main Authors: Gratton, Cristiano, Venkategowda, Naveen K. D., Arablouei, Reza, Werner, Stefan
Format: Conference Proceeding
Language:English
Subjects:
ADMM
consensus
Convergence
Convex functions
Distributed databases
distributed estimation
Estimation
Programming
semidefinite programming
Signal processing algorithms
total least squares
Tuning
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Summary:We propose a new distributed algorithm to solve the total least-squares (TLS) problem when data are distributed over a multi-agent network. To develop the proposed algorithm, named distributed ADMM TLS (DA-TLS), we reformulate the TLS problem as a parametric semidefinite program and solve it using the alternating direction method of multipliers (ADMM). Unlike the existing consensus-based approaches to distributed TLS estimation, DA-TLS does not require careful tuning of any design parameter. Numerical experiments demonstrate that the DA-TLS converges to the centralized solution significantly faster than the existing consensus-based TLS algorithms.
ISSN:2379-190X
DOI:10.1109/ICASSP.2019.8682190