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Broadband power-line communication (BPLC) is recognized as an attractive method for access networks and the orthogonal frequency division multiplexing (OFDM) with dynamic resource allocation is the key technology in combating with the multi-path fading and time-varying characteristics of power line channel. With the goal of fairness in bandwidth and maximum total throughput for all the users, a novel...
As a method of fault diagnosis and state monitoring for HV-power equipments, infrared image analysis has been applied while edge detection is a crucial step of this image application. In this paper, a novel edge detection based on quantum-inspired is proposed. Quantum-inspired edge detection (QIED) is based on concepts and principles of quantum computing such as quits and superposition of states....
The method integrated by independent component analysis (ICA) and empirical mode decomposition (EMD) is proposed in this paper, which can separate the signal from white noise. We used this method to eliminate the white noise from electric power system signals. The detailed courses of construction of virtual noise channel used EMD are described. Based on the characteristic of signals and noise, the...
Indoor power line is considered as one of the most attractive transmission media for home network, because it pervasive exists in almost every residential. In this paper, a novel home network integrated with power line and wireless communication is presented. However, the power line has the hostile channel for transmission high frequency signal. To design home networks better, the channel characteristics...
This paper presents a channel model of the indoor power line for broadband power line communication (BPLC). Considering transmission theory, the two-port network model of power line has been established in this paper. And according to this model, characteristics of power line channel under the different network configuration and terminate loads have been analyzed. The model has been verified with...
The electric power load is inherently nonlinear and nonstationary time series, which has periodicity and randomicity. It is difficult to accurately forecast with a single method. So a hybrid method based on empirical mode decomposition (EMD) and support vector machines (SVMs) was presented in this paper. First, load time series was adaptively decomposed into a series of smooth intrinsic mode functions...
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