in this paper‎, ‎following a very recent‎ ‎and new approach‎, ‎we further generalize recently introduced‎ ‎summability methods‎, ‎namely‎, ‎$i$-statistical convergence and‎ ‎$i$-lacunary statistical convergence (which extend the important‎ ‎summability methods‎, ‎statistical convergence and lacunary‎ ‎statistical convergence using ideals of $mathbb{n}$) and‎ ‎introduce the notions of $i$-statis...

A general convergence analysis of the cascade algorithm, for the determination of a refinable function from its mask, is applied to box splines in which case certain difficulties adherent to the general case can be resolved completely and even elegantly. In the process, the understanding of the convergence of the adjoint process, subdivision, is also enhanced.

In the present paper convergence characteristics of Sample matrix Inversion (SMI) and Least Mean Square (LMS) adaptive beam-forming algorithms (ABFA) are compared for a Smart Antenna System (SAS) in a multipath environment. SAS are employed at base stations for radiating narrow beams at the desired mobile users. The ABFA are incorporated in the digital signal processors for adjusting the weight...

Wireless community these days debate frequently about convergence (next generation) network, a wireless system that is likely to appear after the successful deployment of the current third-generation (3G) systems. Towards convergence of various wireless networks, the integration of universal mobile telecommunication system (UMTS) and wireless local area network (WLAN) plays a major role. Enhanc...

So far various methods for optimization presented and one of most popular of them are optimization algorithms based on swarm intelligence and also one of most successful of them is Particle Swarm Optimization (PSO). Prior some efforts by applying fuzzy logic for improving defects of PSO such as trapping in local optimums and early convergence has been done. Moreover to overcome the problem of i...

We propose a privacy-preserving ensemble infused enhanced Deep Neural Network (DNN) based learning framework in this paper for Internet-of-Things (IoT), edge, and cloud convergence the context of healthcare. In convergence, edge server is used both storing IoT produced bioimage hosting DNN algorithm local model training. The ensembling models. DNN-based training process with dataset suffers fro...

in the present paper, we introduce some new sequence spaces derived by riesz mean and the notions of almost and strongly almost convergence in a real 2-normed space. some topological properties of these spaces are investigated. further, new concepts of statistical convergence which will be called weighted almost statistical convergence, almost statistical convergence and statistical convergence...

Purpose: The goal of this paper is to introduce and discuss the concepts of service convergence and service integration, illustrate them in the context of the medical tourism industry, and link them to factors that contributed to the success of a medical tourism firm. Methodology: The basis for the conceptual development of service convergence and service integration is an in-depth case study o...