For the analytical approximation with Equation 9, described under Analytical Approximation above, the number of operations required for the computation depends on the details of the data as this determines the number of operations.
Table 6 contains the number of operations needed for the computation of four sub-band values for the investigated filter-bank structures.
M f and M g denote the size of the signal and kernel, respectively, c is a constant corresponding to a per-pixel number of arithmetic operations needed for the computation of FFT, and P denotes the number of parts the input data are divided into.
The FFT efficiency has been exploited for the implementation of the block NLMS [16], e.g., for the filtering operation and for the computation of the block gradient estimate, applying suitable constraints in order to avoid circular convolution.
The running time of all operations except for the computations of base cases is thus T(|| s||).
This paper presents several optimization techniques using SIMD operations for the RD cost computations and transforms for variable block sizes.
The paper [4] presents superfast (i.e., with numerical operations) and stable algorithms for the computation of some of the eigenvalues for a real-symmetric and banded matrix with bandwidth, where or for the most interesting division-free algorithms.
Table 2 shows the number of operations that are necessary for the computation of the coefficients for Zernike moments until order 8. Configuration 1 corresponds to the case where (55 values), (45 values), the matrix (45 values) and the, the, the, the, the and the (9 6 = 54 values), that is, 199 values stored.
Simulation results: Noting that the computation overhead of these schemes mainly results from the cryptographic operations, thus the computation time consumed on the cryptographic operations can be used to approximate the efficiency of the schemes for the sake of simplicity.
In SympyCore [ 11] the leading row and column selection rule consists of choosing such a pivot element that minimizes the number of row operations for minimal computation time.
