Motivated by (1.8), Zhao and Yang [10, 12] also studied the following more general algorithm which generates a sequence according to the recursive formula (1.9).
This is a motivation for us to study the following more general algorithm which generate the sequences,, and, respectively, via the formulas (1.13).
We introduce a little more general algorithm as follows.
By using an argument like the method in Theorem 3.10, we have the following more general algorithm and convergence theorem.
The proposed modification refers to the procedure of spatial integration and leads to a more general algorithm involving a weighting parameter.
Also, the tailored solution in Algorithm 4 only applies to HD one-way relaying where SI does not exist, unlike the more general Algorithm 3 which applies even to FD one-way relaying.
In most of the previous studies on the robustness of the standard code [ 12, 22- 244 45] 45], this algorithm was used to generate random alternative codes, sometimes, with modifications to prohibit particular permutations; however, analyses of random code generated with more general algorithms, without the constraint on the block structure, also have been reported [ 13, 52, 53].
Consequently, computer scientists used the increasing computational power of GPUs to implement more general algorithms by expressing them in the aforementioned shader languages.
However, our more general algorithms appear to work well with the Rosa datasets, for which the assumption is reasonable.
In 2009, Saeidi [26] introduced a more general iterative algorithm for finding a common element of the set of solution for a system of equilibrium problems and the set of common fixed points for a finite family of nonexpansive mappings and a nonexpansive semigroup.
for all n = 0,1,2,...... Further, we propose the following iterative method for SCVIP (1a,b) which is more general than Algorithm 2. Let {α n } ⊆ (0,1) be a sequence such that ∑ n = 1 ∞ α n = + ∞ Open image in new window, and let ρ, λ, γ are parameters with positive values.
