Computational equations for the dynamic condensation matrix are derived for each of definitions.
In contrast to deterministic signals that are rigidly periodic, stochastic signals are difficult to be modeled precisely by mathematical functions due to uncertainty in the parameters of the computational equations.
Computational aeroacoustics equations are developed using a Janzen Rayleigh expansion of the compressible flow equations.
A comparison of the two approaches brings forth a key feature of equation-free computation: computational experiments can be easily initialized at will, in contrast to laboratory ones.
To reduce the computational complexity of Equation (13), we employ an approximation technique.
The computational results of Equation 4 are also displayed in Figure 2 (lines).
In summary, the whole NGF method is summarized as follows: At each iteration, the computational cost of Equation 9 is linear with respect to problem size, namely O(n2).
Supposing the values (u_{i}^{n}) have been obtained, the essential ingredients of the computational algorithm for equation (2.27) consist of the following steps: 1. CIP method is used to obtain (u^) a.
Based on the computational results of equation (7), the c' = (r1, r4) was recommended for its two highest values, or r1 (0.4) and r4 (0.33), since other combinations, or (r1, r2), (r1, r3),......, r7, r8), were smaller than (r1, r4).
In order to reduce computational complexity of Equation 8, Gerschgorin Circle theorem [20] can be used since A is full rank and Eigen values of AAH is positive and real.
