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Group tracking based on Markov Chain Monte Carlo particle filter (MCMC-PF) algorithm has high accuracy of individual target tracking and group tracking, but the main problem of MCMC-PF algorithm is calculation burden, that's because it considers all kinds of hypotheses between state vector and measurement vector in the observation model. Therefore, in this paper, we originally use the results of data...
Passive radar exploits third-party commercial transmitters such as frequency modulated signals, television (TV) signals and navigation signals to detect, locate and track targets. In this paper, for the considerations of both large transmitting power and wide coverage area, analog TV signal is selected as the transmitter of the passive radar. Analog TV signal consists of audio signal and visual signal...
Orthogonal Frequency Division Multiplexing (OFDM) is an efficient modulation method which is widely used in many mobile communication systems. Applying OFDM signals to radar systems will make the combination of radar and communication systems in one single system platform possible. In this paper, the auto-correlation and cross-correlation components of the ambiguity function are researched for the...
With the development of radar signal processing, integration of radar communication and guidance design on the hardware becomes popular. Dynamic partial reconfiguration of FPGA can reconfigure part of its logic resource at run time. In this article, an integrated radar signal processing hardware platform was designed, on which both LFM waveform and FSK waveform were processed with method of FPGA dynamic...
Gaussian-Mixture Probability Hypothesis Density (GM-PHD) filter is one of the implementation of PHD filter based on Random Finite Set (RFS). The algorithm performs well in jointly estimating the number of targets and their states with low computation demanding. However, the GM-PHD filter can't provide trajectories of individual targets. This paper proposes two approaches to combine the GM-PHD filter...
Locating a radiant source based on time difference of arrival (TDOA) measurements using spatially separated receivers has wide applications. Although extensive research works have been performed on development of TDOA localization solution, limited attention has been paid to sensor array geometry design. However, the sensor array geometry has a significant influence on the localization accuracy. Therefore,...
The smart substation is an important part of smart grid. By transmitting GOOSE (Generic Object Oriented Substation Event) and MMS (Manufacturing Message Specification) message among devices, the smart substation can realize the functions including, protection, control, alarm etc. Currently available smart substation secondary system's operation and maintenance analysis doesn't take account of the...
Nowadays, smart substation is the main form in the substation's construction and the well-done acceptance work has become an important guarantee for the successful operation of smart substation. The current acceptance work is very complex which need experts and field technicians more cooperation to complete it. This paper analyzes the acceptance work of the smart substation and we propose a new method...
With the increasing coupling of secondary system components in smart substation, the operation management becomes more and more difficult. This paper proposes a graphical display approach of secondary functional components based on “information-event-function” logics. The displayed layout as well as connection relationship, which is accomplished through automatic graphing, clearly describes the logical...
The parallel manipulator has some advantages of high accuracy, high speed and high stiffness etc. It makes up for the shortcomings of serial robot. So the parallel mechanism becomes a potential motion platform with high speed and high accuracy. Six poles parallel robot improves these defects of more singularity, poor load capacity and low stiffness which exist in workspace of the classic plane five...
At present in most field's data sets, spectral clustering community detection algorithm is difficult to predict the number of clustering problems, this paper proposes a community detection algorithm based on multi-domain adaptive spectral clustering (MDASC). Firstly based on the local node density composition, combined with graph edge-betweenness structural similarity matrix, normalized spectral clustering,...
In this paper, a functional damage evaluation system is designed and implemented. The rules of functional damage evaluation for equipment in smart substation follow the human experience problem handling. The electric wiring diagram of primary system and topological graph of secondary equipment are automatically generated. The information collected in online monitoring system is used to discover anomalies...
Protein structure based enzyme class prediction is a useful and challenging task in protein analysis. Here we describe a new method for the prediction of enzyme class based on Rough Sets theory, which is a supervised and rule-based learning method. The method can assign protein function from structure with simple attributes calculated from the primary sequence, such as amino acid compositions and...
To distinguish different level of occupational stress of students and nurses, this paper applied inner composition alignment (IOTA) algorithm to analyse differences between the students' Electroencephalogram (EEG) and the nurses' EEG and to explore the influence of occupational stress on EEG. First, we selected nine cases of students EEG data and the same quantity of nurses EEG data from General Hospital...
For brain function study, it is very important to assess the state of different attention conditions. In this paper, we study a cross-correlation between different attention electroencephalograph (EEG) signals by detrended cross-correlation analysis (DCCA). We use the method to study attention a wave EEG. And, we found that is possible to discriminate the cross-correlation between the meditation state...
In this paper, we proposed a novel optical encryption and decryption method of gray image based on the Fourier computer-generated hologram (CGH) and logical modulation. Since the encryption method using the CGH or the logical modulation alone has a shortness of low security, the proposed novel encryption combines the two methods together. In our encryption processing, the hologram, which is gotten...
In this paper, a novel encryption and decryption method for color images based on the Hadamard transform (HT) and logical modulation has been proposed. Firstly, considering security and efficiency, together, our cryptosystem combined with image compression can reduce encryption time and promote real-time secure image transmission and storage. Then the compressed image is encrypted by logical modulation...
The physiological analysis of electroencephalogram (EEG) signals is of great significance in assessing the activity of the brain function and the physiological state. EEG is a means of clinical examination of brain diseases. Age is one of the important factors that affect the results of the EEG. EEG signal analysis is mainly to analyze the time series of the signal, multiscale entropy (MSE) analysis...
In this paper, we propose a method to analyze epileptic electroencephalogram based on time series that is transformed from improved k-nearest neighbor network. The study of complex networks has become a hot research of electroencephalogram signal. Electroencephalogram time series generated by the network keeps node information of network, so researching the time series from the network can also achieve...
Aiming at studying the influences of epilepsy on brain's nonlinear characteristics, we analyzed the difference between the normal EEG (electroencephalogram) and epileptic EEG from the perspective of nonlinear dynamics. Two sets of data used in this paper, including 16 cases of normal EEG and the same quantity of epileptic EEG, were from General Hospital of Nanjing Military Region. Firstly, on the...
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