Skip to search formSkip to main contentSkip to account menu

Semidefinite programming

Known as: Semi-definite programming, Semidefinite programs 
Semidefinite programming (SDP) is a subfield of convex optimization concerned with the optimization of a linear objective function (an objective… 
Wikipedia (opens in a new tab)

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2009
2009
This work introduces a unified framework for model invalidation and parameter estimation for nonlinear systems. We consider a… 
Highly Cited
2008
Highly Cited
2008
In most sensor network applications, the information gathered by sensors will be meaningless without the location of the sensor… 
Highly Cited
2005
Highly Cited
2005
This paper gives some new stability sufficient conditions. It presents an extension of the classical Lyapunov theory by… 
2004
2004
The inverse eigenvalue problem of constructing real and symmetric square matrices M, C, and K of size $n \times n$ for the… 
2003
2003
  • C. Scherer
  • 2003
  • Corpus ID: 118031373
Robust semi-definite programming problems are know to have a wide range of applications, in particular in robust control. For… 
Highly Cited
2002
Highly Cited
2002
Focuses on the concept of an eventually periodic linear discrete-time system. We derive a necessary and sufficient analysis… 
1995
1995
This paper introduces a novel, image-adaptive, encoding scheme for the baseline JPEG standard. In particular, coefficient… 
Review
1972
Review
1972
Since the appearance of [6] and [7], the theory of linear filtering has experienced a renaissance. This theory, although…