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Radial Basis Function is explored to establish the nonlinear mapping rules for modifying the source speaker features to that of the target speaker.
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ITheaphysicalon to the vibration control of a non-uniformeaningswith bofndary inputhese inveshifting.
Individual gene functions were explored using the NCBI Entrez Gene database.
Considering that blended basis functions have given promising results in multi-resolution-based image fusion, and wavelet basis which is a typical basis function is also widely used in CS, we propose to explore the application of CS image fusion based on blended basis functions.
In addition, the selection of an optimal basis function is conducted to separate the useful basis function terms from the full set of the basis function.
The multivariate adaptive spline basis function was used.
A radial basis function was used as the kernel function.
Radial basis function was chosen as a kernel.
The number of basis functions is set to 100.
By convention, the DC term of the horizontal basis functions is to the left, and the DC term for the vertical basis functions is at the top.
Radial basis function-based transformation model is explored to capture the nonlinear dynamics of the acoustical cues between source and desired target speakers.
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