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[原创] control refine chaotic distribution

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发表于 2022-9-22 19:53:25 来自手机 | 显示全部楼层 |阅读模式

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The element-wise multiplication and division
  and a fraction bar A/B.

adding 1 highlight 8 1 omni light denote respectively the positive and negative parts of A defined as follows:
  The standard NMF model is a low-rank approximation technique for unsupervised multivariate data analysis.
  The multivariate data to decompose are stacked into V,
  whose columns represent the different observations,
  and whose rows represent the different variables.
  W then form a basis and each column of H is the decomposition or encoding of the corresponding column of V into this basis.

looking 3 omni light options  As the model in (14.2) may provide an approximate factorization h = WH of V,
  the aim is to find a factorization that optimizes a given goodness-of-fit measure called
  the Frobenius norm is used to define the following Euclidean cost function:
  factors W and H can be computed with the popular multiplicative updates introduced in [2,
  These updates are derived from a gradient descent scheme with judiciously chosen adaptive steps as follows:
  for which specific multiplicative updates have also been derived [2,

adding shadow effects  NMF algorithms have been applied to various problems in computer vision,
  biomedical data analysis and text classification among others [25].
  the matrix V is in general a time-frequency representa- tion of the sound to analyze.
  The rows and columns represent respectively different
  the decomposition coefficients hij represent the activations of the i -th template at the j -th time-frame.
  a selective sparsity regularization [30],

softening shadow edges  Some authors have also used non-negative decomposition for sound event detec- tion.
  A real-time system to identify the presence and determine the pitch of one or more voices is proposed in [4] and is adapted to sight-reading evaluation of solo instrument in [5].
  A real- time system for polyphonic music transcription is also proposed in [8] and is further developed in [9]
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