Study on hybrid pattern recognition algorithm for modulated signals

Liu, Hongda; He, Pengfei

doi:10.1016/s1005-8885(14)60504-5

Cited by 4 publications

(5 citation statements)

References 4 publications

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“…Depressive symptoms and anxious symptoms had co-morbidity with a strong correlation. The prevalence of Internet addiction among rural left-behind adolescents in this study was slightly higher (17.7%) than that among general adolescents in China (17.1%) (Liu & He, 2019) and about 1.3 times the global prevalence of Internet addiction among adolescents (13.6%) (Fumero et al, 2018).…”

Section: Mediating Effect and Chain-mediating Effect Of Friendship Qu...contrasting

confidence: 64%

“…Depressive symptoms and anxious symptoms had co‐morbidity with a strong correlation. The prevalence of Internet addiction among rural left‐behind adolescents in this study was slightly higher (17.7%) than that among general adolescents in China (17.1%) (Liu & He, 2019) and about 1.3 times the global prevalence of Internet addiction among adolescents (13.6%) (Fumero et al, 2018). These findings confirmed that it is very necessary to elucidate the internal and external psychological assets of the behavioural and psychological problems among the rural left‐behind adolescents.…”

Section: Discussionmentioning

confidence: 49%

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Internet addiction and depressive and anxious symptoms among Chinese rural left‐behind adolescents: Mediating roles of resilience and friendship quality

Shang,

Pang,

Jiang

et al. 2023

Child

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BackgroundRural left‐behind adolescents are more vulnerable to Internet addiction and depressive and anxious symptoms due to the lack of family support and parental supervision. This study was the first to investigate the longitudinal relationships between Internet addiction and depressive and anxious symptoms and to examine the mediating roles of resilience and friendship quality in rural left‐behind adolescents.MethodsIncluded in this study, which was from a longitudinal study conducted five times over 2 years, were 1001 rural left‐behind adolescents. The internationally used scales for depressive and anxious symptoms, Internet addiction, resilience and friendship quality were administered. A structural equation model was used for analysis.ResultsThe prevalence of Internet addiction, depressive and anxious symptoms among rural left‐behind adolescents were 17.7%, 35.8% and 27.6%, respectively. Internet addiction predicted the later depressive and anxious symptoms (β = 0.200, 95% confidence interval [CI]: 0.116–0.274 and β = 0.263, 95% CI: 0.188–0.330). Resilience acted as an independent mediator in the relationships between Internet addiction and depressive and anxious symptoms (β = 0.037 and 0.034, P < 0.01). Resilience and friendship quality played a chain‐mediating role on the longitudinal relationships between Internet addiction and depressive and anxious symptoms (β = 0.011 and 0.010, P < 0.001). The mediating effects accounted for 24.0% and 16.7% of the total effects, respectively.ConclusionResilience and friendship quality play an independent or chain‐mediating role in longitudinal relationships between Internet addiction and depressive and anxious symptoms. The findings inform targeted intervention strategies to improve the mental health of left‐behind adolescents.

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Section: Mediating Effect and Chain-mediating Effect Of Friendship Qu...contrasting

confidence: 64%

Section: Discussionmentioning

confidence: 49%

Internet addiction and depressive and anxious symptoms among Chinese rural left‐behind adolescents: Mediating roles of resilience and friendship quality

Shang,

Pang,

Jiang

et al. 2023

Child

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“…If the visible light blocked by the glass used in the system exceeds the infrared light, the IR correction needs to be adjusted. If the host has not made any infrared correction, you can turn off the infrared measurement in the CHLIST parameter [9].…”

Section: Ambient Lightmentioning

confidence: 99%

Recognition of Piano Play Gesture Based on Infrared Sensor Detection Rod

Wang¹

2023

Atlantis Highlights in Social Sciences, Education and Humanities

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Piano playing gloves are a new intelligent wearable device. The multiinertial sensors in the gloves can sense and analyze the gesture state of piano players in real time, which can make piano learners know whether the playing gestures are standard in real time, thus effectively improving piano learning efficiency and interest, and reducing learning costs. Different from gestures in other application fields, piano playing gestures have the characteristics of diversity, rapidity, great dynamics and strong time-varying. A design scheme of non-contact gesture recognition system is proposed. In this system, infrared and ambient light sensors Si1143 are combined with capacitive touch-sensitive microcontrollers such as C8051F700 and C8051F800 to realize non-contact gesture recognition, which can be used for various actions and gesture detection and distance calibration of target objects.

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“…Reference [10] proposed a new classification method based on high cumulative volume to complete the recognition of MPSK and MQAM in Gaussian channel and fading channel. Reference [11] proposed to extract feature parameters based on high-order cumulants, and applied ant colony algorithm in the design of classifier. Reference [12] proposed the recognition of 2ASK, 2FSK, 2PSK, 4PSK, 4PSK, 4quaternary amplitude modulation (4ASK) and 4FSK based on the instantaneous characteristic parameters after wavelet de-noising.…”

Section: Introductionmentioning

confidence: 99%

Modulation Recognition based on Wavelet Transform and Fractal Theory

Guo¹

2019

IJPE

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With the rapid development of communication technology, digital signal processing and other technologies, wireless communication environment is becoming more and more complex. Communication signals with different frequencies and modulated modes are usually scattered over a wide frequency band. In this paper, an improved algorithm based on wavelet transform and fractal theory is proposed. To improve the traditional fractal theory, wavelet transform is applied to the modulation signal, and then four fractal dimensions (Fractal box dimension, Petrosian fractal dimension, Katz fractal dimension and Sevcik fractal dimension) are used to extract the features. Through the simulation of the six modulation signals generated by Matlab, it can be seen that the recognition rate of the proposed method reaches 90% at the SNR of 2dB. Moreover, by comparing the method of this paper with the short-time Fourier transform and the fractional Fourier transform, we can find that the recognition rate of this method is 3% ~ 10% higher than the two comparison methods. It can be seen that the proposed method can effectively identify different signals in the case of low SNR.

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Study on hybrid pattern recognition algorithm for modulated signals

Cited by 4 publications

References 4 publications

Internet addiction and depressive and anxious symptoms among Chinese rural left‐behind adolescents: Mediating roles of resilience and friendship quality

Internet addiction and depressive and anxious symptoms among Chinese rural left‐behind adolescents: Mediating roles of resilience and friendship quality

Recognition of Piano Play Gesture Based on Infrared Sensor Detection Rod

Modulation Recognition based on Wavelet Transform and Fractal Theory

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