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Given a positive integer k, a social network G and a certain propagation model M, influence maximization aims to find a set of k nodes that has the largest influence spread. The state-of-the-art method IMM is based on the reverse influence sampling (RIS) framework. By using the martingale technique, it greatly outperforms the previous methods in efficiency. However, IMM still has limitations in scalability...
As a key problem in viral marketing, influence maximization has been extensively studied in the literature. Given a positive integer $k$<alternatives> <inline-graphic xlink:href="wang-ieq1-2624734.gif"/></alternatives>, a social network $\mathcal {G}$<alternatives><inline-graphic xlink:href="wang-ieq2-2624734.gif"/> </alternatives> and a certain...
This paper introduces an automated optimization procedure for multiplexers using aggressive space mapping(ASM). Instead of establishing an equivalent circuit model in a circuit analysis software, the parameters extraction is accomplished using Cauchy method to increase the accuracy and stability. The optimization process is controlled by MATLAB and passively implemented in HFSS without manual intervention,...
In this paper, we consider a random wireless sensor network where the sensor nodes are distributed randomly and form clusters to cooperatively transmit data packets using cooperative multi-input-multi-output (CMIMO) technique. We focus on analyzing the overall system performance in terms of packet error rate (PER). And then propose a new node sleep strategy to minimize the overall energy consumption...
A new extraction method for InGaP/GaAs HBTs based on direct optimization is proposed. Through modification of conventional GP formulation, the variations of transport saturation current and ideal forward transit time versus biases are incorporated into the compact model. Rather than intense and complicated iterative optimization, this new parameter extraction methodology realized the united optimization...
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