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133 results on '"Margaliot, M."'

2. Model order reduction for the TASEP Master equation

Author

Pioch, K., Kriecherbauer, T., Margaliot, M., and Grüne, L.

Abstract

The totally asymmetric simple exclusion process (TASEP) is a stochastic model for the unidirectional dynamics of interacting particles on a 1D-lattice that is much used in systems biology and statistical physics. Its master equation describes the evolution of the probability distribution on the state space. The size of the master equation grows exponentially with the length of the lattice. It is known that the complexity of the system may be reduced using mean field approximations. We provide a rigorous derivation and a stochastic interpretation of these approximations and present numerical results on their accuracy for a number of relevant cases.

Published
2024
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10. The low-frequency distortion in D-class amplifiers

Author

Margaliot, M. and Weiss, G.

Subjects
Power amplifiers -- Design and construction, Pulse modulation (Electronics) -- Analysis, Signal processing -- Analysis, Digital signal processor, Business, Computers and office automation industries, Electronics, Electronics and electrical industries
Published
2010

17. Energy dependence of the supralinearity (f(D)max) of peaks 7 and 8 in the high temperature thermoluminescence of LiF:Mg,Ti (TLD-100): Interpretation using the unified interaction model

Author

Datz, H, Horowitz, Yigal S, Epstein, L, Oster, L, Livingstone, Jayde, Horowitz, A, Kol, M, Margaliot, M, Datz, H, Horowitz, Yigal S, Epstein, L, Oster, L, Livingstone, Jayde, Horowitz, A, Kol, M, and Margaliot, M

Abstract

It is demonstrated that the supralinearity of the dose response of glow peaks 7, 8 in the glow curve ofLiF:Mg,Ti (TLD-100) are very strongly dependent on photon/electron energy. Previously published data onf(D)max at photon energies of 1.25 MeV, 100 keV and 8.1 keV effective energy coupled with new dataat w 540 keV using 90Sr/90Y beta rays reveals that the maximum supralinearity f(D)max decreases fromvalues ofw200 andw30 at 1.25MeV, through intermediate values at 540 keV and 100 keV, to values ofw30andw3 at 8.1 keV effective energy. The normalized dose response f(D) for all energies is modeled using theUnified Interaction Model and the dependence of f(D)max on energy is interpreted as arising from strongdependence of the relative intensity of localized recombination on particle energy (ionization density).

Published
2011

45. Biomimicry and Fuzzy Modeling: A Match Made in Heaven.

Author

Margaliot, M.

Abstract

Biomimicry, the design of artificial systems that mimic natural behavior, is recently attracting considerable interest. Biomimicry requires a. reverse engineering process; the behavior of a biological agent is analyzed in order to mimic this behavior in an artificial system. In many cases, biologists have already studied the relevant behavior and provided a detailed verbal description of it. Mimicking the natural behavior can then be reduced to the following problem: how can we convert the given verbal description into a "well-defined mathematical formula or algorithm that can be implemented by an artificial system? Fuzzy modeling (FM), "with its ability to handle and manipulate verbal information, constitutes a natural approach for addressing this problem. The application of FM in this context may lead to a systematic approach for biomimcry, namely, given a verbal description of an animal's behavior (e.g., the foraging behavior of ants), apply FM to obtain a mathematical model of this behavior "which can be implemented by artificial systems (e.g., autonomous robots). The purpose of this position paper is to highlight these issues and to alert the attention of the computational intelligence community to this emerging application of FM. [ABSTRACT FROM PUBLISHER]

Published
2008
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46. The Fuzzy Ant.

Author

Rozin, V. and Margaliot, M.

Abstract

We apply fuzzy modeling to transform a verbal description of the foraging behavior of ants into a well-defined mathematical model. The resulting model is simpler, more plausible, and more amenable to analysis than previously suggested models. We believe that fuzzy modeling may be suitable for addressing biomimicry, that is, the development of artificial products or machines that mimic biological phenomena, in a systematic manner. [ABSTRACT FROM PUBLISHER]

Published
2007
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