76,923 research outputs found
Numerical Verification of Affine Systems with up to a Billion Dimensions
Affine systems reachability is the basis of many verification methods. With
further computation, methods exist to reason about richer models with inputs,
nonlinear differential equations, and hybrid dynamics. As such, the scalability
of affine systems verification is a prerequisite to scalable analysis for more
complex systems. In this paper, we improve the scalability of affine systems
verification, in terms of the number of dimensions (variables) in the system.
The reachable states of affine systems can be written in terms of the matrix
exponential, and safety checking can be performed at specific time steps with
linear programming. Unfortunately, for large systems with many state variables,
this direct approach requires an intractable amount of memory while using an
intractable amount of computation time. We overcome these challenges by
combining several methods that leverage common problem structure. Memory is
reduced by exploiting initial states that are not full-dimensional and safety
properties (outputs) over a few linear projections of the state variables.
Computation time is saved by using numerical simulations to compute only
projections of the matrix exponential relevant for the verification problem.
Since large systems often have sparse dynamics, we use Krylov-subspace
simulation approaches based on the Arnoldi or Lanczos iterations. Our method
produces accurate counter-examples when properties are violated and, in the
extreme case with sufficient problem structure, can analyze a system with one
billion real-valued state variables
Discrete-time recurrent neural networks with time-varying delays: Exponential stability analysis
This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2007 Elsevier LtdThis Letter is concerned with the analysis problem of exponential stability for a class of discrete-time recurrent neural networks (DRNNs) with time delays. The delay is of the time-varying nature, and the activation functions are assumed to be neither differentiable nor strict monotonic. Furthermore, the description of the activation functions is more general than the recently commonly used Lipschitz conditions. Under such mild conditions, we first prove the existence of the equilibrium point. Then, by employing a LyapunovāKrasovskii functional, a unified linear matrix inequality (LMI) approach is developed to establish sufficient conditions for the DRNNs to be globally exponentially stable. It is shown that the delayed DRNNs are globally exponentially stable if a certain LMI is solvable, where the feasibility of such an LMI can be easily checked by using the numerically efficient Matlab LMI Toolbox. A simulation example is presented to show the usefulness of the derived LMI-based stability condition.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Nuffield Foundation of the UK under Grant NAL/00630/G, the Alexander von Humboldt Foundation of Germany, the Natural Science Foundation of Jiangsu Education Committee of China (05KJB110154), the NSF of Jiangsu Province of China (BK2006064), and the National Natural Science Foundation of China (10471119)
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A delay-dependent LMI approach to dynamics analysis of discrete-time recurrent neural networks with time-varying delays
This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2007 Elsevier Ltd.In this Letter, the analysis problem for the existence and stability of periodic solutions is investigated for a class of general discrete-time recurrent neural networks with time-varying delays. For the neural networks under study, a generalized activation function is considered, and the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. By employing the latest free-weighting matrix method, an appropriate LyapunovāKrasovskii functional is constructed and several sufficient conditions are established to ensure the existence, uniqueness, and globally exponential stability of the periodic solution for the addressed neural network. The conditions are dependent on both the lower bound and upper bound of the time-varying time delays. Furthermore, the conditions are expressed in terms of the linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. Two simulation examples are given to show the effectiveness and less conservatism of the proposed criteria.This work was supported in part by the National Natural Science Foundation of China under Grant 50608072, an International Joint Project sponsored by the Royal Society of the UK and the National Natural Science Foundation of China, and the Alexander von Humboldt Foundation of Germany
Asymptotics of work distributions in a stochastically driven system
We determine the asymptotic forms of work distributions at arbitrary times
, in a class of driven stochastic systems using a theory developed by Engel
and Nickelsen (EN theory) (arXiv:1102.4505v1 [cond-mat.stat-mech]), which is
based on the contraction principle of large deviation theory. In this paper, we
extend the theory, previously applied in the context of deterministically
driven systems, to a model in which the driving is stochastic. The models we
study are described by overdamped Langevin equations and the work distributions
in the path integral form, are characterised by having quadratic actions. We
first illustrate EN theory, for a deterministically driven system - the
breathing parabola model, and show that within its framework, the Crooks
flucutation theorem manifests itself as a reflection symmetry property of a
certain characteristic polynomial function. We then extend our analysis to a
stochastically driven system, studied in ( arXiv:1212.0704v2
[cond-mat.stat-mech], arXiv:1402.5777v1 [cond-mat.stat-mech]) using a
moment-generating-function method, for both equilibrium and non - equilibrium
steady state initial distributions. In both cases we obtain new analytic
solutions for the asymptotic forms of (dissipated) work distributions at
arbitrary . For dissipated work in the steady state, we compare the large
asymptotic behaviour of our solution to that already obtained in (
arXiv:1402.5777v1 [cond-mat.stat-mech]). In all cases, special emphasis is
placed on the computation of the pre-exponential factor and the results show
excellent agreement with the numerical simulations. Our solutions are exact in
the low noise limit.Comment: 26 pages, 8 figures. Changes from version 1: Several typos and
equations corrected, references added, pictures modified. Version to appear
in EPJ
The Quantum PCP Conjecture
The classical PCP theorem is arguably the most important achievement of
classical complexity theory in the past quarter century. In recent years,
researchers in quantum computational complexity have tried to identify
approaches and develop tools that address the question: does a quantum version
of the PCP theorem hold? The story of this study starts with classical
complexity and takes unexpected turns providing fascinating vistas on the
foundations of quantum mechanics, the global nature of entanglement and its
topological properties, quantum error correction, information theory, and much
more; it raises questions that touch upon some of the most fundamental issues
at the heart of our understanding of quantum mechanics. At this point, the jury
is still out as to whether or not such a theorem holds. This survey aims to
provide a snapshot of the status in this ongoing story, tailored to a general
theory-of-CS audience.Comment: 45 pages, 4 figures, an enhanced version of the SIGACT guest column
from Volume 44 Issue 2, June 201
Symbolic integration of a product of two spherical bessel functions with an additional exponential and polynomial factor
We present a mathematica package that performs the symbolic calculation of
integrals of the form \int^{\infty}_0 e^{-x/u} x^n j_{\nu} (x) j_{\mu} (x) dx
where and denote spherical Bessel functions of
integer orders, with and . With the real parameter
and the integer , convergence of the integral requires that . The package provides analytical result for the integral in its most
simplified form. The novel symbolic method employed enables the calculation of
a large number of integrals of the above form in a fraction of the time
required for conventional numerical and Mathematica based brute-force methods.
We test the accuracy of such analytical expressions by comparing the results
with their numerical counterparts.Comment: 17 pages; updated references for the introductio
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