Results 281 to 290 of about 251,204 (316)
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Stabilization by Noise Revisited
ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 1990AbstractGiven a d × d matrix A and a d × k matrix B. We investigate how the stability behavior of ẋ = (A + BG(t)) × can be improved by a k × d matrix‐valued white noise process G(t). The analysis is based on the theory of Lyapunov exponents (exponential growth rates) and uses an averaging principle.
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Noise-induced global asymptotic stability
Journal of Statistical Physics, 1990zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Mackey, Michael C. +2 more
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On the stability of the basis pursuit in the presence of noise
Signal Processing, 2006Given a signal S ∈ RN and a full-rank matrix D ∈ RN × L with N < L, we define the signal's overcomplete representation as α ∈ RL satisfying S= Dα. Among the infinitely many solutions of this under-determined linear system of equations, we have special interest in the sparsest representation, i.e., the one minimizing ||α||0.
David L. Donoho, Michael Elad
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2009
This chapter contains sections titled: Noise Types Limiting Displacement Shielding Grounding ...
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This chapter contains sections titled: Noise Types Limiting Displacement Shielding Grounding ...
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Noise Enhanced Stability in an Unstable System
Physical Review Letters, 1996We experimentally detect noise enhanced stability in an unstable physical system. The average escape time from a metastable, periodically driven, system is measured in the stable and unstable regimes in a noisy environment. In the unstable regime, we measure that the average escape time has a maximum for a finite value of the noise intensity.
, Mantegna, , Spagnolo
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On Stability of Linear Estimators in Poisson Noise
2019 53rd Asilomar Conference on Signals, Systems, and Computers, 2019This paper considers estimation of a random variable in Poisson noise. Specifically, the main focus is to assess optimality and near optimality conditions for linear estimators.In the first part of the paper, it is shown that linear estimators are optimal if and only if the underlying prior is a gamma distribution and the dark current parameter is zero.
Alex Dytso, H. Vincent Poor
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Stability of the Tree of Shapes to Additive Noise
2021The tree of shapes (ToS) is a famous self-dual hierarchical structure in mathematical morphology, which represents the inclusion relationship of the shapes (\textiti.e. the interior of the level lines with holes filled) in a grayscale image. The ToS has already found numerous applications in image processing tasks, such as grain filtering, contour ...
Boutry, Nicolas, Tochon, Guillaume
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Stability and stabilization of stochastic systems with multiplicative noise
International Journal of Control, Automation and Systems, 2011In this paper, stability and stabilization of linear stochastic time-invariant systems are studied based on spectrum technique. Firstly, the relationship among mean square exponential stability, asymptotical mean square stability, second-order moment exponential stability and the spectral location of the systems is revealed with the help of a spectrum ...
Huiying Sun, Meng Li, Weihai Zhang
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Stabilization of a nonlinear system by multiplicative noise
Physical Review A, 1991The effect of multiplicative colored noise on the stabilization of a bistable system is studied numerically. In particular, numerical simulation of a much discussed theoretical study carried out by Graham and Schenzle [Phys. Rev. A 26, 1676 (1982)] is presented.
, Billah, , Shinozuka
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Stability and stabilization of discrete systems with multiplicative noise
1997 European Control Conference (ECC), 1997In this paper we consider the problem of the stabilization of unstable stochastic difference systems by the addition of multiplicative noise. We illustrate the possibilities of stabilization by uniformly and normally distributed multiplicative noises. Then we present different approaches to the problem of finding sufficient conditions for stability and
Mile Milisavljevic, Erik I. Verriest
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