The aim of the present paper is to introduce a Kantorovich-type modification of the q-discrete beta operators and to investigate their statistical and weighted statistical approximation properties. Rates of statistical convergence by means of the modulus of continuity and the Lipschitz-type function are also established for operators. Finally, we construct a bivariate generalization of the operator and also obtain the statistical approximation properties. MSC: 41A25; 41A36
If temporal information were the primary factor in speech recognition with cochlear implants then SAS should consistently produce higher speech recognition scores than CIS. That was not the case, however, because most CIS users performed significantly worse with the SAS strategy on all speech tests. Hence, there seems to be a trade-off between improving the temporal resolution with an increasing number of simultaneous channels and introducing distortions from electrical-field interactions. Performance for some CI users improved when the number of simultaneous channels increased to two (PPS strategy) and four (QPS strategy). The improvement with the PPS and QPS strategies must be due to the higher rates of stimulation. The above results suggest that CIS users are less likely to benefit with the SAS strategy, and they are more likely to benefit from the PPS and QPS strategies, which provide higher rates of stimulation with small probability of channel interaction.
The aim of this paper is to define a new iteration scheme $N^v_1$ which converges to a fixed point faster than some previously existing methods such as Picard, Mann, Ishikawa, Noor, SP, CR, S, Picard-S, Garodia, $K$ and $K^*$ methods etc. The effectiveness and efficiency of our algorithm is confirmed by numerical example and some strong convergence, weak convergence, $T$-stability and data dependence results for contraction mapping are also proven. Moreover, it is shown that differential equation with retarted argument is solved using $N^v_1$ iteration process.
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