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As discussed in Section 3.1, we have opted for using a square mixing matrix, with little loss of generality.
Non-negative matrix factorization [15, 16] attempts to find a mixing matrix (with sparse weights [17, 18]) and a source matrix with non-negative elements so that the reconstruction error is minimized.
The basic noise free blind source separation generative model in the time domain is x t) = H s(t), wherein, omitting the time index t for convenience, x = [ x 1, x 2, …, x m ] T is the observed mixed signal vector, s = [ s 1, s 2, …, s n ] T is the source signal vector, H is the mixing matrix with m × n dimension, and T denotes the transpose operator.
With linear ICA, X is modeled as a linear mixture of independent sources, i.e.,
All instantaneous mixtures were obtained using the same mixing matrix with positive coefficients.
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The experimental synthesis of designed pools can benefit from using optimized starting sequences, mixing matrices, and pool fractions associated with each of the constructed pools as a guide.
Thus, in those time-frequency bins, where source is dominant, the associated basis vector should correspond to the column of the mixing matrix associated with source.
The sexual mixing matrix, along with a description of other model components (e.g., population demographic characteristics, economic costs of care, health-related quality of life) are described elsewhere [ 14].
This group [ 40, 41] has recently developed an approach for engineering sequence pools that links RNA sequence space regions with corresponding structural distributions via a "mixing matrix" approach combined with a graph theory analysis.
Therefore, whitening merely transforms the original source separation problem with mixing matrix A into a new problem with mixing matrix B A. The advantage is that B A is an orthogonal mixing matrix, and its estimation becomes easier[7].
The mixing matrix is now 4×4 with independent Gaussian entries.
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