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Best_Learn_Matlab_8.9901

于 2009-10-07 发布 文件大小:300KB
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代码说明:

  lEARN MATL lEARN MATL lEARN MATL lEARN MATL

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    2013-03-21 09:18:11下载
    积分:1
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    to binirazition pictures in matlab
    2012-10-10 18:40:38下载
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    matlab在物理化学科学的应用,有相关的统计分析和聚类模型(matlab in physical and chemical science and application of relevant statistical analysis and clustering model)
    2008-01-04 18:07:36下载
    积分:1
  • LMSnew
    最小均方误差迭代算法和最小二乘算法的仿真程序。适用初学者(least mean square and recursive least square. appropriate for elementary learners.)
    2014-11-04 22:46:50下载
    积分:1
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    LMS三角定位迭代加权算法 LMS三角定位迭代加权算法 LMS三角定位迭代加权算法(LMS triangulation iterative weighting algorithm LMS triangulation iterative weighting algorithm LMS triangulation iterative weighting algorithm)
    2013-12-03 09:05:26下载
    积分:1
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    利用扩展卡尔曼进行状态估计 状态向量四维 测量向量二维 误差为高斯白噪声(The use of extended Kalman state vector for state estimation of two-dimensional four-dimensional vector measurement error is Gaussian white noise)
    2007-09-06 19:59:30下载
    积分:1
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    2011-04-14 11:10:23下载
    积分:1
  • sampling_square
    this code is to sample the signal
    2011-05-27 16:40:00下载
    积分:1
  • MATLABfangzheng123
    《MATLAB仿真技术与应用》是我见过该类型最好的一本书,这是我那最新版的配套光盘("MATLAB simulation technology and application," I have seen the best of this type of a book. This is my latest version of the matching CD)
    2007-04-09 01:37:26下载
    积分:1
  • src-fusion
    A. Fusion at the Feature Extraction Level The data obtained from each sensor is used to compute a feature vector. As the features extracted from one biometric trait are independent of those extracted from the other, it is reasonable to concatenate the two vectors into a single new vector. The primary benefit of feature level fusion is the detection of correlated feature values generated by different feature extraction algorithms and, in the process, identifying a salient set of features that can improve recognition accuracy [14]. The new vector has a higher dimension and represents the identity of the person in a different hyperspace. Eliciting this feature set typically requires the use of dimensionality reduction/selection methods and, therefore, feature level fusion assumes the availability of a large number of training data.
    2013-03-14 16:40:42下载
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