Sentence examples for algorithm is proved in from inspiring English sources

Then, the global convergence of the presented algorithm is proved in detail.

Weak convergence of this algorithm is proved in a Hilbert space.

The algorithm is proved in theory and has shown its high performance over several real-world benchmark data sets.

The main result, that is, the strong convergence of the regularization algorithm, is proved in Section 3.

A new nonmonotone hybrid conjugate gradient algorithm is presented and the global convergence of the algorithm is proved in Section 2.

Finally, global convergence of the proposed algorithm is proved in theory, and its performance is investigated on some global optimization functions, UCI datasets and magnetic resonance images (MRIs), compared with existing state-of-the-art algorithms.

Under suitable conditions some strong convergence theorems for the sequences generated by the algorithm are proved in the setting of infinite-dimensional Hilbert spaces.

The KLT algorithm was proved in [1] and [22] by subjective tests to perform well in terms of preserving speech intelligibility for normal hearing listeners and improving speech intelligibility significantly for cochlear implant users in regard to recognition of sentences corrupted by stationary noises, respectively.

Strong convergence of the sequences generated by these algorithms is proved in uniformly smooth and strictly convex real Banach spaces with the Kadec-Klee property.

In this way, various well-constrained problems with a few exceptions are solved, over-constrained scenes and input data contradictory to some well-known mathematical theorems are detected, and the algorithm is proved successful in many under-constrained cases as well.

This algorithm is proved to be rigorous in mathematics and not complicated.