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Then, the sparse representation coefficients matrix of training sample sets for specific cloud type was used to form a projection subspace.
R is the autocorrelation matrix of training samples.
where z l and ∑ l are the mean vector and covariance matrix of training samples, respectively.
For the nth subcarrier, we may, therefore, consider that we transmit a matrix of training signals, X n, where x n,q,m is the element in the qth row and mth column.
The memory requirements for wKSVD are much larger and correspond to the entire matrix of training signals, O(d N) or O(m N), since the iteratively weighted dictionary update repeatedly accesses residuals, coefficients and masks.
Following the standard machine learning paradigm, the feed-forward back-propagation ANN models were trained by feeding a matrix of training data complete with the input and target values.
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So then I can get a matrix of train times versus test times.
The parameters for the prior are obtained from the MLLR transformation matrices of training speakers {W1,…,W S }: w ̄ ( i ) = 1 S ∑ s w s, ( i ) Σ ( i ) = 1 S − 1 ∑ s w s, ( i ) − w ̄ ( i ) T w s, ( i ) − w ̄ ( i ) (58).
While MPCA decomposes the data matrix consisting of training samples, our proposed MDA aims to decompose the LDA projection matrix : (21).
2: Learn dictionary inner product A T A and sparse coefficient matrix Y of training instances by Algorithm 4. 3: Train a classifier f using Y (in the feature space spanned by columns of A ). {prediction step:} 1: Normalize each new instance to have unit l2 norm.
SVMs were trained using a pre-computed kernel matrix of all training proteins.
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