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Computation of piecewise quadratic Lyapunov functions for hybrid systems
TLDR
This paper presents a computational approach to stability analysis of nonlinear and hybrid systems. Expand
Piecewise quadratic stability of fuzzy systems
TLDR
We present an approach to stability analysis of fuzzy systems based on continuous and piecewise quadratic Lyapunov functions. Expand
Piecewise Linear Control Systems
This thesis treats analysis and design of piecewise linear control systems. Piecewise linear systems capture many of the most common nonlinearities in engineering systems, and they can also be usedExpand
Simultaneous routing and resource allocation via dual decomposition
TLDR
We formulate the simultaneous routing and resource allocation (SRRA) problem as a convex optimization problem, and exploit problem structure to derive efficient solution methods. Expand
Low power, low delay: Opportunistic routing meets duty cycling
TLDR
We introduce ORW, a practical opportunistic routing scheme for wireless sensor networks. Expand
Optimal Parameter Selection for the Alternating Direction Method of Multipliers (ADMM): Quadratic Problems
TLDR
In this paper we find the optimal algorithm parameters that minimize the convergence factor of the alternating direction method of multipliers iterates in the context of ℓ2-regularized minimization and constrained quadratic programming. Expand
Computation of piecewise quadratic Lyapunov functions for hybrid systems
TLDR
We present a computational approach to stability analysis of nonlinear and hybrid systems. Expand
Cross-layer optimization of wireless networks using nonlinear column generation
  • M. Johansson, Lin Xiao
  • Computer Science, Mathematics
  • IEEE Transactions on Wireless Communications
  • 1 November 2006
TLDR
We consider the problem of finding the jointly optimal end-to-end communication rates, routing, power allocation and transmission scheduling for wireless networks. Expand
Piecewise linear quadratic optimal control
TLDR
The use of piecewise quadratic cost functions is extended from stability analysis of piece wise linear systems to performance analysis and optimal control. Expand
The Convergence of Sparsified Gradient Methods
TLDR
We prove that, under analytic assumptions, sparsifying gradients by magnitude with local error correction provides convergence guarantees, for both convex and non-convex smooth objectives, for data-parallel SGD. Expand
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