Venkataramanan Balakrishnan
Purdue University
162 Papers
1.4K Citations
Venkataramanan Balakrishnan is an academic researcher from Purdue University. The author has contributed to research in topics: Convex optimization & Linear system. The author has an hindex of 31, co-authored 162 publications. Previous affiliations of Venkataramanan Balakrishnan include University of California, Irvine & University of Maryland, College Park.
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Papers
Linear matrix inequalities in robustness analysis with multipliers
TL;DR: In this paper, a number of standard robustness tests can be reinterpreted as special cases of the application of the passivity theorem with the appropriate choice of multipliers, using convex optimization over linear matrix inequalities.
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Robust steady-state filtering for systems with deterministic and stochastic uncertainties
TL;DR: This work presents filtering algorithms that solve each of these problems, with the filter parameters determined via convex optimization based on linear matrix inequalities, and demonstrates the performance of these robust algorithms on a numerical example consisting of the design of equalizers for a communication channel.
Linear matrix inequalities in analysis with multipliers
Venkataramanan Balakrishnan,Y. Huang,Andy Packard,John Doyle +3 more
- 29 Jun 1994
TL;DR: In this article, a number of standard robustness tests can be reinterpreted as special cases of the application of the passivity theorem with the appropriate choice of multipliers, using convex optimization over linear matrix inequalities.
Numerical Methods for H 2 Related Problems
Eric Feron,Venkataramanan Balakrishnan,Stephen Boyd,L. El Ghaoui +3 more
- 24 Jun 1992
TL;DR: An interior point algorithm for the solution of these convex programs with a finite number of variables is presented and its application with the standard LQR design is illustrated.
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Superfast Divide-and-Conquer Method and Perturbation Analysis for Structured Eigenvalue Solutions
TL;DR: This work presents a superfast divide-and-conquer method for finding all the eigenvalues as well as allThe eigenvectors (in a structured form) of a class of symmetric matrices with off-diagonal ranks or n...
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