A Novel Wireless Statistical Division Multiplexing Communication System and Performance Analysis

Wei Zhao,Yuehong Shen,Pengcheng Xu,Jiangong Wang,Zhigang Yuan,Yimin Wei,Wei Jian,Hui Li 보안공학연구지원센터 2014 International Journal of Future Generation Communi Vol.7 No.5

Blind Source Separation of Instantaneous Mixture of Delayed Sources Using High-Order Taylor Approximation

Wei Zhao,Zhi-Gang Yuan,Yue-hong Shen,Yufan Cao,Yimin Wei,Pengcheng Xu,Wei Jian 한국전자통신연구원 2015 ETRI Journal Vol.37 No.4

This paper deals with the problem of blind source separation (BSS), where observed signals are a mixture of delayed sources. In reference to a previous work, when the delay time is small such that the first-order Taylor approximation holds, delayed observations are transformed into an instantaneous mixture of original sources and their derivatives, for which an extended second-order blind identification (SOBI) approach is used to recover sources. Inspired by the results of this previous work, we propose to generalize its first-order Taylor approximation to suit higher-order approximations in the case of a large delay time based on a similar version of its extended SOBI. Compared to SOBI and its extended version for a first-order Taylor approximation, our method is more efficient in terms of separation quality when the delay time is large. Simulation results verify the performance of our approach under different time delays and signal-to-noise ratio conditions, respectively.

A New Ambiguity Elimination Method for BSS Block Signals in Time Domain

Wei Zhao,Fengshan Wang,Yuehong Shen,Yuanyuan Wu,Zhigang Yuan,Pengcheng Xu,Pengcheng Xu,Yimin Wei,Wei Jian 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.11

This paper deals with the ambiguity problem of blind source separation (BSS) in the case where continuously received mixture signals are split in time and processed block by block. Due to the inherent permutation and scaling ambiguities of BSS, tying the separated components at each adjacent time blocks doesn’t recover the original source signals correctly in general. Inspired by the Permutation Method of reconstructing source signal blocks in time domain, a new ambiguity elimination approach is proposed in this paper. This method aims to concatenate the separated components in adjacent blocks by artificially setting contrast blocks for each adjacent time blocks. The core idea of this method is to utilize the associativity between components recovered from contrast blocks and corresponding adjacent blocks. Compared with Permutation Method, the main advantage of this new method consists in the fact that it is much more efficient in terms of separation quality and computational speed. Besides, a tradeoff can be adjusted between separation quality and computational speed by choosing different length of contrast blocks. Real-life experiments are performed to validate the performance of this method on the wireless communication system with two transmitting and receiving antennas.

A Novel and Efficient Wireless Communication System

Wei Zhao,Yuehong Shen,Zhigang Yuan,Yimin Wei,Wei Jian 보안공학연구지원센터 2015 International Journal of Future Generation Communi Vol.8 No.5

This paper aims to construct a novel wireless communication system, in which source signals are transmitted simultaneously in the same frequency band. The transmitted signals are only required to be statistically independent or statistically distinguished. Therefore, the source signals can be recovered at the receiver by utilizing the classical algorithms of blind source separation (BSS) and independent component analysis (ICA) such as the fast fixed-point algorithm (FastICA). On the one hand, because the source signals are transmitted simultaneously in the same frequency band, the spectrum efficiency of this novel system is much higher than those of time division multiplexing (TDM), frequency division multiplexing (FDM), and code division multiplexing (CDM) systems, in which TDM, FDM and CDM signals are limited in time interval, frequency band and code. On the other hand, inspired by recently proposed reference-based schemes, the reference signals are introduced to the classical separation algorithms of BSS and ICA, which makes this novel system much more efficient than classical ones in terms of computational speed. The performance of this new system is validated through realistic experiments. Additionally, it is theoretically shown that the information content of all the source signal inputs can be recovered by this novel wireless communication system.

Efficiency Analysis of Gear System Based on Gear Surface Micro-topography

Wei Liu,Yimin Shao,Hongwu Li,Yan Cheng,Jin Xu 제어로봇시스템학회 2018 제어로봇시스템학회 국제학술대회 논문집 Vol.2018 No.10

In order to accurately calculate the gear transmission efficiency, a new efficiency evaluation method is proposed considering the 3D micro-topography of the tooth surface. Firstly, a digital microsystem is used to obtain the surface micro-topography of gears. The roughnesses of the gears at different meshing positions are then calculated according to the tooth surface micro-topography parameters and the gear meshing principle. Subsequently, the calculated roughnesses are substituted into the gear system dynamic model with the ROMAX software employed, and the distribution of friction coefficient and efficiencies of gear system can be simulated at different input torques and roughnesses. The simulation results show that the greater the surface roughness, the lower the efficiency of gear transmission. Conversely, the greater the torque, the greater the efficiency of the gear transmission. Finally, to further validate the effectiveness of the proposed method, efficiency experiments at same working conditions are carried out and a sound comparative analysis of previous studies is launched. The results show that the proposed method is effective with an error of less than 2%.

PERTURBATION ANALYSIS OF THE MOORE-PENROSE INVERSE FOR A CLASS OF BOUNDED OPERATORS IN HILBERT SPACES

Deng, Chunyuan,Wei, Yimin Korean Mathematical Society 2010 대한수학회지 Vol.47 No.4

Let $\cal{H}$ and $\cal{K}$ be Hilbert spaces and let T, $\tilde{T}$ = T + ${\delta}T$ be bounded operators from $\cal{H}$ into $\cal{K}$. In this article, two facts related to the perturbation bounds are studied. The first one is to find the upper bound of $\parallel\tilde{T}^+\;-\;T^+\parallel$ which extends the results obtained by the second author and enriches the perturbation theory for the Moore-Penrose inverse. The other one is to develop explicit representations of projectors $\parallel\tilde{T}\tilde{T}^+\;-\;TT^+\parallel$ and $\parallel\tilde{T}^+\tilde{T}\;-\;T^+T\parallel$. In addition, some spectral cases related to these results are analyzed.

RSNT-cFastICA for Complex-Valued Noncircular Signals in Wireless Sensor Networks

( Changliang Deng ),( Yimin Wei ),( Yuehong Shen ),( Wei Zhao ),( Hongjun Li ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.10

This paper presents an architecture for wireless sensor networks (WSNs) with blind source separation (BSS) applied to retrieve the received mixing signals of the sink nodes first. The little-to-no need of prior knowledge about the source signals of the sink nodes in the BSS method is obviously advantageous for WSNs. The optimization problem of the BSS of multiple independent source signals with complex and noncircular distributions from observed sensor nodes is considered and addressed. This paper applies Castella’s reference-based scheme to Novey’s negentropy-based algorithms, and then proposes a novel fast fixed-point (FastICA) algorithm, defined as the reference-signal negentropy complex FastICA (RSNT-cFastICA) for complex-valued noncircular-distribution source signals. The proposed method for the sink nodes is substantially more efficient than Novey’s quasi-Newton algorithm in terms of computational speed under large numbers of samples, can effectively improve the power consumption effeciency of the sink nodes, and is significantly beneficial for WSNs and wireless communication networks (WCNs). The effectiveness and performance of the proposed method are validated and compared with three related BSS algorithms through theoretical analysis and simulations.

PERTURBATION ANALYSIS OF THE MOORE-PENROSE INVERSE FOR A CLASS OF BOUNDED OPERATORS IN HILBERT SPACES

Chunyuan Deng,Yimin Wei 대한수학회 2010 대한수학회지 Vol.47 No.4

Let H and K be Hilbert spaces and let T,T = T+δTbe bounded operators from H into K. In this article, two facts related to the perturbation bounds are studied. The first one is to find the upper bound of ∥T+T − T+T∥, which extends the results obtained by the second author and enriches the perturbation theory for the Moore-Penrose inverse. The other one is to develop explicit representations of projectors ∥T+T − T+T∥and ∥T+T − T+T∥. In addition, some spectral cases related to these results are analyzed.

Building Cooling Load Prediction Based on Time Series Method and Neural Networks

Junhua Zhuang,Yimin Chen,Xiaoxia Shi,Dong Wei 보안공학연구지원센터 2015 International Journal of Grid and Distributed Comp Vol.8 No.4

Predicting the load in a building is essential for the optimal control of heating, ventilating and air-conditioning (HVAC) systems that use Ice Thermal Energy Storage (ITES) technology and also for cost and energy reduction of the non-storage systems. To solve the problems of the low accuracy of prediction by a single method, and most load predictions focusing on short-time prediction that cause reducing the practical significance, the application of the combined prediction method of time series and neural networks is presented in this paper. A case study shows that high accuracy is achieved by using the combined prediction model based on these two methods compared with the time series method in predicting the building load for longer time.

Model predictive control of double-input buck converters

Chen, Yunzhu,Lu, Yimin,Luo, Wei The Korean Institute of Power Electronics 2021 JOURNAL OF POWER ELECTRONICS Vol.21 No.6

The control system of a multiple-input dc-dc converter should ensure the stability of output voltage and reasonably distribute the power of multiple-input voltage sources. In addition, there is mutual coupling between multiple closed control loops, which makes the design of the control system difficult. Based on the ability of model predictive control (MPC) to deal with constraints explicitly, a model predictive control algorithm based on the state-space averaging method is proposed for a double-input buck converter. First, a state-space averaging model of a double-input buck converter is established. Then, considering the power management of two input power supplies, a model predictive controller is designed based on the model by combining the input constraints with the objective function. Both simulation and experimental results show that the system has good steady-state accuracy and fast dynamic response characteristics under the action of model predictive controller.