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Semidefinite Programming Relaxations of Non-Convex Problems in Control and Combinatorial Optimization
Semidefinite Programming Relaxations Non-Convex Problems Control Combinatorial Optimization
2015/7/13
We point out some connections between applications of semidefinite programming in control and in combinatorial optimization. In both fields semidefinite programs arise as convex relaxations of NP-hard...
FIR Filter Design via Spectral Factorization and Convex Optimization
FIR Filter Design Spectral Factorization Convex Optimization
2015/7/13
We consider the design of finite impulse response (FIR) filters subject to upper and lower bounds on the frequency response magnitude. The associated optimization problems, with the filter coefficient...
Analysis of Linear Systems with Saturation Using Convex Optimization
Analysis Linear Systems Saturation Convex Optimization
2015/7/13
We show how linear matrix inequalities (LMI) can be used to perform local stability and performance analysis of linear systems with saturating elements. This leads to conservative information on stabi...
Joint Optimization of Communication Rates and Linear Systems
Communication systems control over networks convex optimization quantization noise
2015/7/10
We consider a linear control system in which several signals are transmitted over communication channels with bit-rate limitations. With the coding and medium access schemes of the communication syste...
Automatic Code Generation for Real-Time Convex Optimization
Automatic Code Generation Real-Time Convex Optimization
2015/7/9
This chapter concerns the use of convex optimization in real-time embedded systems, in areas such as signal processing, automatic control, real-time estimation, real-time resource allocation and decis...
Real-Time Convex Optimization in Signal Processing
Real-Time Convex Optimization Signal Processing
2015/7/9
Convex optimization has been used in signal processing for a long time, to choose coefficients for use in fast (linear) algorithms, such as in filter or array design; more recently, it has been used t...
CVXGEN:A Code Generator for Embedded Convex Optimization
Convex optimization Code generation Embedded optimization
2015/7/9
CVXGEN is a software tool that takes a high level description of a convex optimization problem family, and automatically generates custom C code that compiles into a reliable, high speed solver for th...
Robust Optimization of Adiabatic Tapers for Coupling to Slow-Light Photonic-Crystal Waveguides
Computational electromagnetic methods Optoelectronics Photonic crystal waveguides Photonic integrated circuits
2015/7/9
We investigate the design of taper structures for coupling to slow-light modes of various photonic-crystal waveguides while taking into account parameter uncertainties inherent in practical fabricatio...
A Primal-Dual Operator Splitting Method for Conic Optimization
Primal-Dual Operator Splitting Method Conic Optimization
2015/7/9
We develop a simple operator splitting method for solving a primal conic optimization problem; we show that the iterates also solve the dual problem. The resulting algorithm is very simple to describe...
Block Splitting for Distributed Optimization
Distributed optimization · Alternating direction method of multipliers Operator splitting Proximal operators Cone programming Machine learning
2015/7/9
This paper describes a general purpose method for solving convex optimization problems in a distributed computing environment. In particular, if the problem data includes a large linear operator or ma...
Convex Optimization in Julia
Convex programming automatic verifcation symbolic computation multiple dispatch
2015/7/9
This paper describes Convex.jl, a convex optimization modeling framework in Julia. Convex.jl translates problems from a user-friendly functional language into an abstract syntax tree describing the pr...
LARGE-SCALE LINEARLY CONSTRAINED OPTIMIZATION
Large-scale Systems Linear Constraints Linear Programming
2015/7/3
An algorithm for solving large-scale nonlinear' programs with linear constraints is presented.
The method combines efficient sparse-matrix techniques as in the revised simplex method
with stable q...