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12 results on '"Wang, Linghuan"'

5. Parameters estimation of linear FM signal based on matching Fourier transform

Author

Li Zhao, Ma Hong-guan, Wang Linghuan, Ai Ming-shun, and Zhang Xin-yu

Subjects
symbols.namesake, Signal processing, Signal-to-noise ratio, Fourier transform, Noise (signal processing), Estimation theory, symbols, Electronic engineering, Sine, Doppler effect, Signal, Algorithm, Mathematics
Abstract

The maximum amplitude of matching Fourier transform (MFT) spectrum based on re-sampling of sine (single pulse, SP) signal reflected the frequency of the signal. The analysis of the MFT spectrum of SP signal reflected the MFT theories, from which a method to estimate the frequency of SP signal was proposed; The similarity of the MFT spectrum of the SP and linear FM (LFM) signal was analyzed, then the parameter estimation of LFM signal was presented; The characteristic of promoting the MFT spectrum after adding windows was illustrated, so a method to improve the precision of estimation parameter by adding windows was proposed. The experiments and simulations show the efficiency of the parameters estimation of LFM signal.

Published
2008

6. A Method to Detect Multi-components Linear FM Signal

Author

Ma Hongguang, Zhang Jiawen, Ai Ming-shun, and Wang Linghuan

Subjects
Radon transform, Estimation theory, business.industry, Computation, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Pattern recognition, Signal, Time–frequency analysis, Support vector machine, Cluster labeling, Detection theory, Artificial intelligence, business, Mathematics
Abstract

The support vector clustering (SVC) algorithm was introduced to get the number of the pinnacles in the result of the time-frequency analysis and Radon transform of the multi-component linear FM (LFM) signal, and to finish the detection of the components of the LFM signal. Meanwhile, the preprocessing to reduce the points' number of the input data-set for SVC, was proposed to improve the computation efficiency. And a novel cluster labeling method was developed to improve the SVC algorithm. The simulation results depict that the SVC-Radon-time-frequency approach is efficient for the detection and parameter estimation of the multi-component LFM signal with low SNR

Published
2006

7. Fast Estimation of BPSK Signal Parameters

Author

Wang Linghuan, Ai Ming-shun, Zhao Xunhui, Li Zhao, and Ma Hongguang

Subjects
Wavelet, law, Computer science, Pulse-Doppler radar, Pulse compression, Electronic engineering, Binary code, Data_CODINGANDINFORMATIONTHEORY, Radar, Signal, Algorithm, Phase-shift keying, law.invention
Abstract

Based on the principle of correlation detection, a new algorithm of recognizing the binary-phase coded pulse compression radar signal is proposed, which is simple to realize. The simulation shows that the method can effectively complete the BPSK signal parameters estimation, and is superior to that using wavelet, under low signal-to-noise rate (SNR).

Published
2006

11. Multicomponent linear FM signal detection based on support vector clustering

Author

Wang Linghuan, Li Qi, Ma Hongguang, and Li Zheng

Subjects
Radon transform, business.industry, Estimation theory, Computation, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Pattern recognition, Signal, Time–frequency analysis, Support vector machine, Cluster labeling, Detection theory, Artificial intelligence, business, Mathematics
Abstract

The support vector clustering (SVC) algorithm was introduced to get the number of the pinnacles in the result of the time-frequency analysis and Radon transform of the multicomponent linear FM (LFM) signal, and to fulfil the detection of the components of the LFM signal. Meanwhile, an approach called near zero mean, for reducing the point number of the input data-set for SVC, was proposed to improve the computation efficiency. And a novel cluster labeling method was developed to improve the SVC algorithm. The simulation results depict that the SVC-radon-time-frequency approach is efficient for the detection and parameter estimation of the multi-components LFM signal

12. Association between Human Blood Proteome and the Risk of Myocardial Infarction.

Author

Wang L, Zhang W, Fang Z, Lu T, Gu Z, Sun T, Han D, Wang Y, and Cao F

Abstract

Background: The objective of this study is to estimate the causal relationship between plasma proteins and myocardial infarction (MI) through Mendelian randomization (MR), predict potential target-mediated side effects associated with protein interventions, and ensure a comprehensive assessment of clinical safety., Methods: From 3 proteome genome-wide association studies (GWASs) involving 9775 European participants, 331 unique blood proteins were screened and chosed. The summary data related to MI were derived from a GWAS meta-analysis, incorporating approximately 61,000 cases and 577,000 controls. The assessment of associations between blood proteins and MI was conducted through MR analyses. A phenome-wide MR (Phe-MR) analysis was subsequently employed to determine the potential on-target side effects of protein interventions., Results: Causal mediators for MI were identified, encompassing cardiotrophin-1 (CT-1) (odds ratio [OR] per SD increase: 1.16; 95% confidence interval [CI]: 1.13-1.18; p = 1.29 × 10 - 31 ), Selenoprotein S (SELENOS) (OR: 1.16; 95% CI: 1.13-1.20; p = 4.73 × 10 - 24 ), killer cell immunoglobulin-like receptor 2DS2 (KIR2DS2) (OR: 0.93; 95% CI: 0.90-0.96; p = 1.08 × 10 - 5 ), vacuolar protein sorting-associated protein 29 (VPS29) (OR: 0.92; 95% CI: 0.90-0.94; p = 8.05 × 10 - 13 ), and histo-blood group ABO system transferase (NAGAT) (OR: 1.05; 95% CI: 1.03-1.07; p = 1.41 × 10 - 5 ). In the Phe-MR analysis, memory loss risk was mediated by CT-1, VPS29 exhibited favorable effects on the risk of 5 diseases, and KIR2DS2 showed no predicted detrimental side effects., Conclusions: Elevated genetic predictions of KIR2DS2 and VPS29 appear to be linked to a reduced risk of MI, whereas an increased risk is associated with CT-1, SELENOS, and NAGAT. The characterization of side effect profiles aids in the prioritization of drug targets. Notably, KIR2DS2 emerges as a potentially promising target for preventing and treating MI, devoid of predicted detrimental side effects., Competing Interests: The authors declare no conflict of interest., (Copyright: © 2024 The Author(s). Published by IMR Press.)

Published
2024
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