1-Bit DOA Estimation Algorithm for Strictly Non-Circular Sources

Teng, Liping; Wang, Qing; Chen, Hua

doi:10.1109/lcomm.2021.3072490

Cited by 8 publications

(2 citation statements)

References 21 publications

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“…Recently, the exploitation of non-circularity has received increasing interest in DOA estimation. Non-circular (NC) signals such as amplitude modulation signal (AM), binary phase shift keying (BPSK), Gaussian filter minimum frequency shift keying (GMSK), etc., are often used in multiple-input-multiple-output (MIMO) radar and wireless communication systems (Wan et al, 2021;Teng et al, 2021;Shu et al, 2020;Zhang et al, 2021). A non-circular signal holds a non-zero secondorder (SO) conjugate moment in addition to the SO moment.…”

Section: Intruductionmentioning

confidence: 99%

Geometric Algebra based 2D-DOA Estimation for Non-circular Signals with an Electromagnetic Vector Array

Wang,

Feng,

et al. 2024

Digital Signal Processing

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Section: Intruductionmentioning

confidence: 99%

Geometric Algebra based 2D-DOA Estimation for Non-circular Signals with an Electromagnetic Vector Array

Wang,

Feng,

et al. 2024

Digital Signal Processing

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“…Neural network can arbitrarily fit the relationship between input and output, and there is no corresponding system error that leads to a large estimation error [ 31 , 32 ]. The estimation accuracy of neural network in mental health training is relatively high, and its network model size can be balanced and adjusted with the estimation accuracy, so as to control its model size for subsequent deployment and application in embedded systems.…”

Section: Research On Estimation Algorithm Based On Artificial Intelli...mentioning

confidence: 99%

Feasibility Analysis and Countermeasures of Psychological Health Training Methods for Volleyball Players Based on Artificial Intelligence Technology

Jin

2022

Journal of Environmental and Public Health

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In the process of volleyball players’ mental health training, there exists the problem of low parameter accuracy. In order to further improve the accuracy of mental health training methods, based on artificial intelligence calculation, the neural network and long and short-term memory network were used to analyze the model. Estimation algorithm was used to describe the data, and finally, the optimization model was obtained to describe the feasibility study of mental health. In addition, the relevant data were used to verify and analyze the model. The research shows that in the time update curve, with the increase of the model state, the corresponding curve on the whole first presents a fluctuating trend of different degrees. The increase of model state will make the corresponding time value gradually tend to flat. The fluctuation of the corresponding time index is obvious. Indicators corresponding to the status update curve show an obvious linear change trend with the increase in time, and the overall linear characteristics are obvious. This shows that when time is constant, the relationship between the corresponding parameter and the state value conforms to the linear law. The corresponding state index gradually increases and eventually tends to be stable. Through the analysis, it can be seen that the proportion of different indicators under the effect of artificial intelligence and the calculation results are different. The parameters show an obvious linear variation trend, indicating that the corresponding model parameters can well reflect the data changes. Finally, the accuracy of the model is verified by the method of experimental comparison. The relevant research results can provide a new model and a method for volleyball players’ mental health training.

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