作者机构:
[谭清懿; 杨开建; 乔冠瑾] Department of Electrical Engineering, University of South China, Hengyang, 421001, China;[杜丹] Department of Mathematics and Physics, University of South China, Hengyang, 421001, China;[潘光祖; 周华; 龚学余] Department of Nuclear Science and Technology, University of South China, Hengyang, 421001, China
通讯机构:
[Du, D.] D;Department of Mathematics and Physics, China
作者:
Pang, Lihui;Tang, Yilong;Tan, Qingyi;Liu, Yulang;Yang, Bin
期刊:
EURASIP Journal on Advances in Signal Processing,2022年2022(1):1-25 ISSN:1687-6180
通讯作者:
Pang, Lihui(sunshine.plh@hotmail.com)
作者机构:
[Tan, Qingyi; Tang, Yilong; Yang, Bin; Pang, Lihui; Liu, Yulang] Univ South China, Sch Elect Engn, Hengyang 421001, Peoples R China.;[Pang, Lihui] Sungkyunkwan Univ, Dept Software, Suwon 440746, South Korea.
通讯机构:
[Lihui Pang] S;School of Electrical Engineering, University of South China, Hengyang, China<&wdkj&>Department of Software, Sungkyunkwan University, Suwon, South Korea
关键词:
Blind signal separation;Kernel density estimation;Maximum likelihood estimation;Neural networks;Time–frequency overlapped signal
摘要:
The blind signal separation (BSS) algorithm obtains each original/source signal from the observed signal collected by the receiving antenna or sensor. Objective/loss/cost function and optimization method are two key parts of BSS algorithm. Modifying the objective function and optimization from the perspective of neural network (NN) is a novel concept in BSS domain.
$$L_2$$
regularization is adopted as a term of maximum likelihood estimation (MLE)-based objective function like in Liu et al.(Sensors 21(3):973, 2021); however, we modified the probability density function (PDF) term of the objective function and used the kernel density estimation method for time–frequency overlapped digital communication signal. Multiple optimizers are studied in this paper, and we figure out the right optimizer for our application scenario. A varies of comparison experiments—whoseseparation results will be providedinforms of correlation coefficient and performance index—are carried out, which indicate our method can converge quickly and achieve satisfactory separation results with performance index (PI) lower than 0.02 when signal-to-noise ratio (SNR) no less than 10dB. Additionally, it demonstrates performance of our method is better than that of typical separation—FastICA, especially for the lower SNR environment, and it shows that our method is not sensitive to the frequency overlap level (FOL) of the source signal, even FOL as high as
$$100\%$$
; it still can get high-precision separation results with
$$\textrm{PI}<0.02$$
.
摘要:
Quantum interference effects in the unmodulated quantum systems with light-matter interaction have been widely studied, such as electromagnetically induced transparency (EIT) and Autler-Townes splitting (ATS). However, the similar quantum interference effects in the Floquet systems (i.e., periodically modulated systems), which might cover rich new physics, were rarely studied. In this article, we investigate the quantum interference effects in the Floquet two- and three-level systems analytically and numerically. We show a coherent destruction tunneling effect in a lotuslike multipeak spectrum with a Floquet two-level system, where the intensity of the probe field is periodically modulated with a square-wave sequence. We demonstrate that the multipeak split into multiple transparency windows with tunable quantum interference if the Floquet system is asynchronously controlled via a third level. Based on phenomenological analysis with Akaike information criterion, we show that the symmetric central transparency window has a similar mechanism to the traditional ATS or EIT depending on the choice of parameters, additional with an extra degree of freedom to control the quantum interference provided by the modulation period. The other transparent windows are shown to be asymmetric, different from the traditional ATS and EIT windows. These nontrivial quantum interference effects open up a scope to explore the applications of the Floquet systems.
摘要:
Nowadays, falling is a growing threat to the elderly. This paper combines millimeter wave radar technology, machine learning algorithm, wireless communication technique and cloud platform to realize a fall detection system. In this project, the millimeter wave radar is used to sample the human posture point cloud data, and we create a data set that consist of point of clouds of two different human poses. Random forest and BP neural network are used to train the fall detection model. The system will send the human posture point data to the trained model and realize the fall detection. Besides, the system will use 4G communication technology to transform the data to the web cloud platform. This web page serves as an warning function, which can report the acceleration, speed and other information. According to our experiments, the millimeter wave radar system that we built in this paper can effectively detect human point cloud, and can send human point cloud data packets to the recognition model to detect human falls. In machine learning part, both Random forest and BP neural network models show very strong robustness after repeated adjusting parameters. Random forest has the advantages of light weight and interpretability, which can reach 93% recognition accuracy. The recognition accuracy of BP neural network is even up to 95%, which is higher than other detection models in previous works. Besides, BP neural network model also has higher recall rate in the categories of human falls, which fully meets the requirements of this project.
摘要:
Based on the detected vibration signal, a measurement system was designed to solve the current problem of closed centrifuge speed measurement. The system collected and adjusted the signal collected by the vibration sensor, and then send it to the control unit STM32 for spectrum analysis to get the speed frequency. The sampling data was analysed and processed in PC through serial communication. Programs were written to achieve data sampling, filtering and storage, and the important parameters such as acceleration waveforms, vibration frequency and actual speed were displayed on the screen. The experimental results show that the system can accurately calculate the real-time speed of the closed centrifuge according to the measured vibration signals, which has the advantages of high stability, detection accuracy and real-time performance.
作者机构:
[Li, Longjin; Jia, Lei] Univ South China, Dept Elect Engn, Hengyang, Peoples R China.
会议名称:
25th International Conference on Electrical Machines and Systems (ICEMS)
会议时间:
NOV 29-DEC 02, 2022
会议地点:
Rajamangala Univ Technol Lanna, Chiang Mai, THAILAND
会议主办单位:
Rajamangala Univ Technol Lanna
会议论文集名称:
International Conference on Electrical Machines and Systems ICEMS
关键词:
Brushless doubly-fed generator;Pole-changing;Finite element
摘要:
In this paper, a nested-loop rotor brushless doubly-fed generator (BDFG) with improved stator single winding pole-changing design scheme is presented. The BDFG is simulated at 400 rpm and 600 rpm through finite element (FE) method. It is found that the improved stator single winding pole-changing design scheme is effective in reducing the machine harmonic contents and improving the PW generated voltage, CW current waveforms quality.
摘要:
Visual inspection techniques for rail surface defects have become prevalent approaches to obtain information on rail surface damage. However, uneven illumination leads to illegibility of local information, and the change of the wheel-rail area results in the changeful background of the rail surface, both of which pose challenges to the visual inspection. This paper proposes a novel algorithm that detects rail surface defects via partitioned edge features (PEF). PEF eliminates the effect of uneven illumination by effectively extracting edge features and building homogeneous background on the rail surface. In the process of edge feature extraction, the thresholding based on adaptive partition of rail surface (APRS) plays an indispensable role. In APRS, the rail surface is adaptively partitioned into three types of regions according to the wheel-rail contact degree. After that, the dynamic threshold is set adaptively for each region type on the basis of the prior information of defect proportion. Subsequently, based on neighborhood information and fuzzy decision, the spatial information of adjacent pixels and the direction information of fracture edges are utilized to realize the effective recovery of incomplete defect contours. In addition, defect contours are precisely filled via a flexible combination of morphological hole filling operation and defect region extraction based on improved background difference. The accuracy of this PEF algorithm was confirmed by experiments and comparisons with related algorithms. The experiment results show that PEF detects defects with 92.03% recall and 88.49% precision, which achieves higher accuracy than the established detection algorithms for rail surface defects.