Sentence examples for multiplying the data from inspiring English sources

Another method, called subcarriers weighting (SW) [13, 14], minimizes the signal OOB interference level by multiplying the data subcarriers by optimized real weighting coefficients.

These windows are essentially multiplying the data samples in time and will result in a convolution of the true spectrum with the spectrum of the window.

The "overall" sustainability of each alternative can be calculated by multiplying the data of Table 5 (performance) by those of Table 6 (weights).

By multiplying the data signal with the spreading signal, each baseband information bit is spread to N c chips where N c is the number of spreading sequence samples.

If D denotes the diagonal matrix containing the eigenvalues of the covariance matrix of the data and V denotes an orthonormal matrix which has, in its columns, the corresponding eigenvectors, then whitening can be performed in a PCA-like manner by multiplying the data x t) by a matrix B, where[7] B = D − 1 / 2 V T. (4).

Thus, each genetic perturbation could be assayed for impact on multiple cellular subsystems and/or for multiple reporters within the same system, greatly multiplying the data "bang" for the experimental "buck".

Step 5: Multiply the data matrix D (m, n) with the Scaling Matrix G (m, n) element-by-element wise to obtain GG={ D}_{Mtimes N }mathbf{o}kern0.49em{G}_{Mtimes N} (11).

The author [11] then multiplies the data (f_{1j}) with the new trial function, which is nothing else, but characteristic function of positive time, and represents the wavelet signal in terms of this product.

As it can be observed, the difference between both expressions is in the factors Δi,m and Δi,m + M that multiply the data signal, assuming that the CFO and the channel remain nearly constant over the M OFDM symbols.

What the post doesn't really get into, but is pretty much a foregone conclusion given the sophistication of the tools they're showing off, is how to further multiply the data's value by essentially making up the environment out of whole cloth.

Essentially, the multitaper method attempts to reduce the variance of spectral estimates by pre-multiplying the data with several orthogonal tapers known as Slepian functions.