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    AUTOMATICA
    2007
    95views more  AUTOMATICA 2007»
    Unbiased minimum-variance input and state estimation for linear discrete-time systems with direct feedthrough
    13 years 10 months ago
    Unbiased minimum-variance input and state estimation for linear discrete-time systems with direct feedthrough
    Download  ftp.esat.kuleuven.ac.be
    This paper extends previous work on joint input and state estimation to systems with direct feedthrough of the unknown input to the output. Using linear minimum-variance unbiased ...
    Steven Gillijns, Bart De Moor
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    EOR
    2007
    88views more  EOR 2007»
    The geometry and number of the root invariant regions for linear systems
    13 years 10 months ago
    The geometry and number of the root invariant regions for linear systems
    Download  www.ipu.ru
    The stability domain is a feasible set for numerous optimization problems. D-decomposition technique is targeted to describe the stability domain in the parameter space for linear...
    Elena N. Gryazina
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    GLOBECOM
    2007
    IEEE
    100views Communications» more  GLOBECOM 2007»
    Reduced Complexity Sequence Detection of Continuous Phase Modulation Represented as the Linear Superposition of Amplitude Modula
    14 years 4 months ago
    Reduced Complexity Sequence Detection of Continuous Phase Modulation Represented as the Linear Superposition of Amplitude Modula
    Download  people.eecs.ku.edu
    The Laurent Decomposition expresses any binary single-h CPM waveform as the summation of a finite number of pulse amplitude modulated components, and this result has been useful i...
    Marilynn P. Wylie-Green, Erik Perrins
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    SDM
    2008
    SIAM
    144views Data Mining» more  SDM 2008»
    Active Learning with Model Selection in Linear Regression
    13 years 11 months ago
    Active Learning with Model Selection in Linear Regression
    Download  hrstc.org
    Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
    Masashi Sugiyama, Neil Rubens
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    CORR
    2002
    Springer
    78views Education» more  CORR 2002»
    Linear-Time Algorithms for Computing Maximum-Density Sequence Segments with Bioinformatics Applications
    13 years 10 months ago
    Linear-Time Algorithms for Computing Maximum-Density Sequence Segments with Bioinformatics Applications
    Download  www.csie.ntu.edu.tw
    an abstract optimization problem arising from biomolecular sequence analysis. For a sequence A of pairs (ai, wi) for i = 1, . . . , n and wi > 0, a segment A(i, j) is a consecu...
    Michael H. Goldwasser, Ming-Yang Kao, Hsueh-I Lu
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