Mechanical Vibration Signal Denoising Using Quantum-Inspired Standard Deviation Based on Subband Based Gaussian Mixture Model
المؤلفون المشاركون
Xu, Aidong
Huang, Wenqi
Li, Peng
Chen, Huajun
Meng, Jiaxiao
Guo, Xiaobin
المصدر
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-03-27
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
Aiming at improving noise reduction effect for mechanical vibration signal, a Gaussian mixture model (SGMM) and a quantum-inspired standard deviation (QSD) are proposed and applied to the denoising method using the thresholding function in wavelet domain.
Firstly, the SGMM is presented and utilized as a local distribution to approximate the wavelet coefficients distribution in each subband.
Then, within Bayesian framework, the maximum a posteriori (MAP) estimator is employed to derive a thresholding function with conventional standard deviation (CSD) which is calculated by the expectation-maximization (EM) algorithm.
However, the CSD has a disadvantage of ignoring the interscale dependency between wavelet coefficients.
Considering this limit for the CSD, the quantum theory is adopted to analyze the interscale dependency between coefficients in adjacent subbands, and the QSD for noise-free wavelet coefficients is presented based on quantum mechanics.
Next, the QSD is constituted for the CSD in the thresholding function to shrink noisy coefficients.
Finally, an application in the mechanical vibration signal processing is used to illustrate the denoising technique.
The experimental study shows the SGMM can model the distribution of wavelet coefficients accurately and QSD can depict interscale dependency of wavelet coefficients of true signal quite successfully.
Therefore, the denoising method utilizing the SGMM and QSD performs better than others.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Xu, Aidong& Huang, Wenqi& Li, Peng& Chen, Huajun& Meng, Jiaxiao& Guo, Xiaobin. 2018. Mechanical Vibration Signal Denoising Using Quantum-Inspired Standard Deviation Based on Subband Based Gaussian Mixture Model. Shock and Vibration،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1215306
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Xu, Aidong…[et al.]. Mechanical Vibration Signal Denoising Using Quantum-Inspired Standard Deviation Based on Subband Based Gaussian Mixture Model. Shock and Vibration No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1215306
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Xu, Aidong& Huang, Wenqi& Li, Peng& Chen, Huajun& Meng, Jiaxiao& Guo, Xiaobin. Mechanical Vibration Signal Denoising Using Quantum-Inspired Standard Deviation Based on Subband Based Gaussian Mixture Model. Shock and Vibration. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1215306
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1215306
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر