Journal ArticleDOI
On the stability of Lagrange programming neural networks for satisfiability problems of prepositional calculus
Masahiro Nagamatu,Torao Yanaru +1 more
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This paper theoretically analyze the stability and the convergence property of one of the Lagrange programming neural networks (LPPH) when it is applied to a satisfiability problem (SAT) of prepositional calculus and proves that the solutions of the SAT are the equilibrium points of the LPPH and vice versa.About:
This article is published in Neurocomputing.The article was published on 1996-10-01. It has received 34 citations till now. The article focuses on the topics: Gradient descent & Simulated annealing.read more
Citations
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Journal ArticleDOI
Optimization hardness as transient chaos in an analog approach to constraint satisfaction
TL;DR: In this article, the authors propose a mapping of k-SAT into a deterministic continuous-time dynamical system with a unique correspondence between its attractors and the k SAT solution clusters, and show that beyond a constraint density threshold, the analog trajectories become transiently chaotic.
Journal ArticleDOI
Gases Brownian Motion Optimization: an Algorithm for Optimization (GBMO)
TL;DR: A new algorithm for optimization inspired by the gases brownian motion and turbulent rotational motion is introduced, called Gases Brownian Motion Optimization (GBMO), which is created using the features of gas molecules.
Journal ArticleDOI
An event-based architecture for solving constraint satisfaction problems
TL;DR: It is shown that this parallel analogue/digital hardware architecture specifically designed to solve constraint satisfaction problems can yield state-of-the-art performance on random SAT problems under reasonable assumptions on the implementation.
Book ChapterDOI
A Survey on Analog Models of Computation.
Olivier Bournez,Amaury Pouly +1 more
TL;DR: A survey on analog models of computations, which considers both approaches, often intertwined, with a point of view mostly oriented by computation theory.
Journal ArticleDOI
Robust MIMO Radar Target Localization based on Lagrange Programming Neural Network
TL;DR: Two modifications based on the LPNN framework are proposed, which include a differentiable proximate l1-norm function and a locally competitive algorithm that outperforms several existing schemes.
References
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Journal ArticleDOI
Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Journal ArticleDOI
Neural computation of decisions in optimization problems
John J. Hopfield,David W. Tank +1 more
TL;DR: Results of computer simulations of a network designed to solve a difficult but well-defined optimization problem-the Traveling-Salesman Problem-are presented and used to illustrate the computational power of the networks.
Journal ArticleDOI
A learning algorithm for boltzmann machines
TL;DR: A general parallel search method is described, based on statistical mechanics, and it is shown how it leads to a general learning rule for modifying the connection strengths so as to incorporate knowledge about a task domain in an efficient way.
Journal ArticleDOI
A Computing Procedure for Quantification Theory
Martin Davis,Hilary Putnam +1 more
TL;DR: In the present paper, a uniform proof procedure for quantification theory is given which is feasible for use with some rather complicated formulas and which does not ordinarily lead to exponentiation.