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    » Radial function based kernel design for time-frequency distr...
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    TSP
    2010
    111views Artificial Intelligence» more  TSP 2010»
    Radial function based kernel design for time-frequency distributions
    13 years 28 days ago
    Radial function based kernel design for time-frequency distributions
    Download  users.cecs.anu.edu.au
    Sandun Kodituwakku, Rodney A. Kennedy, Thushara D....
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    CW
    2003
    IEEE
    120views Distributed And Parallel Com...» more  CW 2003»
    Mesh Generation and Refinement of Polygonal Data Sets
    13 years 11 months ago
    Mesh Generation and Refinement of Polygonal Data Sets
    Download  www.karlson.ru
    This paper presents work in progress and continues a project devoted to developing shape modeling system based on implementation of radial based function (RBF) technology. In this...
    Vladimir V. Savchenko, Irina B. Semenova, Nikita K...
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    NA
    2008
    78views more  NA 2008»
    A walk through energy, discrepancy, numerical integration and group invariant measures on measurable subsets of euclidean space
    13 years 6 months ago
    A walk through energy, discrepancy, numerical integration and group invariant measures on measurable subsets of euclidean space
    Download  math.georgiasouthern.edu
    (A) The celebrated Gaussian quadrature formula on finite intervals tells us that the Gauss nodes are the zeros of the unique solution of an extremal problem. We announce recent re...
    S. B. Damelin
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    TVLSI
    2008
    108views more  TVLSI 2008»
    Unified Convolutional/Turbo Decoder Design Using Tile-Based Timing Analysis of VA/MAP Kernel
    13 years 6 months ago
    Unified Convolutional/Turbo Decoder Design Using Tile-Based Timing Analysis of VA/MAP Kernel
    Download  access.ee.ntu.edu.tw
    To satisfy the advanced forward-error-correction (FEC) standards, in which the Convolutional code and Turbo code may co-exit, a prototype design of a unified Convolutional/Turbo de...
    Fan-Min Li, Cheng-Hung Lin, An-Yeu Wu
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    CVPR
    2004
    IEEE
    243views Computer Vision» more  CVPR 2004»
    Incremental Density Approximation and Kernel-Based Bayesian Filtering for Object Tracking
    14 years 8 months ago
    Incremental Density Approximation and Kernel-Based Bayesian Filtering for Object Tracking
    Download  www.caip.rutgers.edu
    Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
    Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...
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