On the Asymptotic Behavior of Solutions of Differential Systems

There are many studies on the asymptotic behavior of solutions of differential equations. In the present paper, we consider another aspect of this problem, namely, the rate of the asymptotic convergence of solutions.Асимптотичній поведінці розв'язків диференціальних рівнянь присвячено чимало досліджень. У даній роботі проблему розглянуто з іншого боку, а саме, з точки зору швидкості асимптотичної збіжності розв'язків

Improving Graph Convolutional Networks with Transformer Layer in social-based items recommendation

In this work, we have proposed an approach for improving the GCN for predicting ratings in social networks. Our model is expanded from the standard model with several layers of transformer architecture. The main focus of the paper is on the encoder architecture for node embedding in the network. Using the embedding layer from the graph-based convolution layer, the attention mechanism could rearrange the feature space to get a more efficient embedding for the downstream task. The experiments showed that our proposed architecture achieves better performance than GCN on the traditional link prediction task

An Efficient Transmission Power Design for SWIPT Multi-antenna Network Integrated by an Intelligent Reflecting Surface

In this work, intelligent reflecting surface (IRS) is integrated to improve the transmission power in the simultaneous wireless information and power transfer (SWIPT) system with hybrid time-switching (TS) users. The considered scenario includes one base station (BS), one IRS, and multiple TS users, where the BS transmits the information and energy signals to the receivers with IRS assistance. The sum transmission power minimization problem is formulated under the quality-of-service constraints of data rate and energy harvesting amount at the TS users and the equal time-switching periods. The successive convex approximation and alternating optimization methods are exploited to construct efficient algorithms for finding the suboptimal precoding beamforming vectors at the BS and the phase shifts at the IRS elements. Finally, the numerical results show convergence and significant improvement in performance as compared to conventional baseline schemes