A holographic reduction transforms the computation to matchgates by a linear transformation that maps to (a tensor product space of) a linear space of dimension 2ℓ.
In this paper, a novel PDF estimation based method is proposed, which equivalently transforms the computation of these two indices into that of the unconditional and conditional fractional moments of model output.
Step, the DCT transform, completes the computation of the MFCC coefficients.
Compared with the classical wavelet transform, the LWT requires less computation and memory, and can produce integer-to-integer wavelet transform.
The core is to transform the time-domain correlation computation between the received signal and the local pseudo code into the multiplication calculation in frequency domain by using the circle correlation theorem, thus greatly reducing the acquisition time.
Specifically, compared to the wavelet-based method [7, 8], which is computation expensive in decomposing the image into different frequency bands and computation of transform, the proposed image definition measure based on fuzzy entropy is more efficient and applicable in practical image measurement system.
Furthermore, the implementation of Gaussian filter is transformed into the computation of the nonlinear numerical integrals in the proposed framework.
It is an eigenvector-based multivariate analysis tool to explain variance of the multivariate data and further to reduce computation burden and transform the original multivariate data to a smaller and more succinct set of variables, namely principal components (PCs), with orthometric and uncorrelated natures (Zhao et al. 2014).
Second order transformation schemes with relative ease and less computation are employed to transform the fourth order governing equation of thin plates between the two domains.
Such characteristic greatly minimizes the complexity of the transform computation procedure, by allowing its computation using only 16-bit integer addition and shift operations.
