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    » An NP-Hardness Result for Nonlinear Systems
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    TSP
    2010
    114views Artificial Intelligence» more  TSP 2010»
    Modeling and identification of nonlinear systems in the short-time fourier transform domain
    13 years 2 months ago
    Modeling and identification of nonlinear systems in the short-time fourier transform domain
    Download  sipl.technion.ac.il
    Abstract--In this paper, we introduce a novel approach for improved nonlinear system identification in the short-time Fourier transform (STFT) domain. We first derive explicit repr...
    Yekutiel Avargel, Israel Cohen
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    AUTOMATICA
    2008
    78views more  AUTOMATICA 2008»
    Exact determinations of the maximal output admissible set for a class of nonlinear systems
    13 years 7 months ago
    Exact determinations of the maximal output admissible set for a class of nonlinear systems
    Download  www.nt.ntnu.no
    This paper is concerned with obtaining necessary and sufficient conditions for fulfilling specified state and control pointwise-in-time constraints against a certain class of nonli...
    Kenji Hirata, Yoshito Ohta
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    ISSAC
    1997
    Springer
    142views Mathematics» more  ISSAC 1997»
    The Structure of Sparse Resultant Matrices
    13 years 11 months ago
    The Structure of Sparse Resultant Matrices
    Download  comet.lehman.cuny.edu
    Resultants characterize the existence of roots of systems of multivariate nonlinear polynomial equations, while their matrices reduce the computation of all common zeros to a prob...
    Ioannis Z. Emiris, Victor Y. Pan
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    GECCO
    2005
    Springer
    138views Optimization» more  GECCO 2005»
    Artificial immune system for solving generalized geometric problems: a preliminary results
    14 years 1 months ago
    Artificial immune system for solving generalized geometric problems: a preliminary results
    Download  www.cs.bham.ac.uk
    Generalized geometric programming (GGP) is an optimization method in which the objective function and constraints are nonconvex functions. Thus, a GGP problem includes multiple lo...
    Jui-Yu Wu, Yun-Kung Chung
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    EUSFLAT
    2009
    245views Fuzzy Logic» more  EUSFLAT 2009»
    Universal Approximation of a Class of Interval Type-2 Fuzzy Neural Networks Illustrated with the Case of Non-linear Identificati
    13 years 5 months ago
    Universal Approximation of a Class of Interval Type-2 Fuzzy Neural Networks Illustrated with the Case of Non-linear Identificati
    Download  www.eusflat.org
    Neural Networks (NN), Type-1 Fuzzy Logic Systems (T1FLS) and Interval Type-2 Fuzzy Logic Systems (IT2FLS) are universal approximators, they can approximate any non-linear function....
    Juan R. Castro, Oscar Castillo, Patricia Melin, An...
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