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Parameter Estimation for Blur Image Combining Defocus and Motion Blur using Cepstrum Analysis 被引量:5
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作者 周曲 颜国正 王文兴 《Journal of Shanghai Jiaotong university(Science)》 EI 2007年第6期700-706,共7页
The degraded parameters recognition is very important for the restoration of blurred images. There are two common types of blurs for most camera systems. One is the defocus blur due to the optical system's defocus... The degraded parameters recognition is very important for the restoration of blurred images. There are two common types of blurs for most camera systems. One is the defocus blur due to the optical system's defocus phenomenon and the other is the motion blur due to the relative movement between the objectives and the camera. Compared with the recognition for the blurred image with only one blur model, the parameter estimation for the picture combining defocus and motion blur models is a more complicated mission. A method was proposed for computer to estimate the parameters of defocus blur and motion blur in cepstrum area simultaneously. According to characters of both blur models in the frequency domain, an adjustment approach was suggested in the frequency area and then convert to the cepstrum field to increase the accuracy of measurement. 展开更多
关键词 point SPREAD function (PSF) DEFOCUS motion BLUR cepstrum
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Extraction of Echo Characteristics of Underwater Target Based on Cepstrum Method 被引量:3
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作者 Hongjian Jia Xiukun Li +1 位作者 Xiangxia Meng Yang Yang 《Journal of Marine Science and Application》 CSCD 2017年第2期216-224,共9页
The analysis and characteristic extraction of target echo characteristics are important in underwater target detection and recognition. Rigid acoustic scattering components are generally used as major echo contributor... The analysis and characteristic extraction of target echo characteristics are important in underwater target detection and recognition. Rigid acoustic scattering components are generally used as major echo contributors with relatively stable characteristic information. Previous studies focus on echo characteristics from a single angle, thereby limiting the amount of extracted characteristic information. This paper aims to establish a full-angle rigid echo components model and overcome the difficulty of the extraction of time delay characteristics of narrow-band acoustic scattering echoes. On the basis of the analysis of the target echo highlight model, the echo characteristics of rigid acoustic scattering components are extracted in the cepstrum domain, and a wavelet process is proposed to enhance the effect of time delay estimation. Experimental data indicate that the extracted time delay characteristics accord with the rigid echo characteristics of underwater target, thereby validating the effectiveness of the cepstrum method. 展开更多
关键词 UNDERWATER target rigid scattering ECHOES time delay CHARACTERISTICS cepstrum wavelet enhancement ECHO characteristic
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Simulating Study of Dynamic Load Spectra Identification Method of Machinery in Cepstrum Domain 被引量:9
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作者 HONG Cong-hua QIAO Shu-yun WU Miao 《Journal of China University of Mining and Technology》 EI 2006年第1期22-24,共3页
Based on the platform of Matlab and the theory of digital signal processing, we propose a method in the cepstrum domain for dynamic load spectra identification of machinery. We demonstrate that the dynamic load spectr... Based on the platform of Matlab and the theory of digital signal processing, we propose a method in the cepstrum domain for dynamic load spectra identification of machinery. We demonstrate that the dynamic load spectra can be identified from the response signal of the system, based on cepstra. An ARMA model is built based on the harmonic retrieval by high-order spectra. The coefficients of a Green function are determined and the window width can be estimated. Finally the effectiveness of the method is validated by simulation results. 展开更多
关键词 cepstrum dynamic load spectrum identification high-order spectra simulation
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Detection and Classification on Amateur Drones Based on Cepstrum of Radio Frequency Signal 被引量:4
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作者 GUAN Xiangmin MA Jianxiang ZHANG Weidong 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2021年第4期597-606,共10页
As a prospective component of the future air transportation system,unmanned aerial vehicles(UAVs)have attracted enormous interest in both academia and industry.However,small UAVs are barely supervised in the current s... As a prospective component of the future air transportation system,unmanned aerial vehicles(UAVs)have attracted enormous interest in both academia and industry.However,small UAVs are barely supervised in the current situation.Crash accidents or illegal airspace invading caused by these small drones affect public security negatively.To solve this security problem,we use the back-propagation neural network(BPNN),the support-vector machine(SVM),and the k-nearest neighbors(KNN)method to detect and classify the non-cooperative drones at the edge of the flight restriction zone based on the cepstrum of the radio frequency(RF)signal of the drone’s downlink.The signal from five various amateur drones and ambient wireless devices are sampled in an electromagnetic clean environment.The detection and classification algorithm based on the cepstrum properties is conducted.Results of the outdoor experiments suggest the proposed workflow and methods are sufficient to detect non-cooperative drones with an average accuracy of around 90%.The mainstream downlink protocols of amateur drones can be classified effectively as well. 展开更多
关键词 drone detection radio frequency signal cepstrum machine learning
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A bearing fault feature extraction method based on cepstrum pre-whitening and a quantitative law of symplectic geometry mode decomposition 被引量:2
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作者 Chen Yiya Jia Minping Yan Xiaoan 《Journal of Southeast University(English Edition)》 EI CAS 2021年第1期33-41,共9页
In order to extract the fault feature of the bearing effectively and prevent the impact components caused by bearing damage being interfered with by discrete frequency components and background noise,a method of fault... In order to extract the fault feature of the bearing effectively and prevent the impact components caused by bearing damage being interfered with by discrete frequency components and background noise,a method of fault feature extraction based on cepstrum pre-whitening(CPW)and a quantitative law of symplectic geometry mode decomposition(SGMD)is proposed.First,CPW is performed on the original signal to enhance the impact feature of bearing fault and remove the periodic frequency components from complex vibration signals.The pre-whitening signal contains only background noise and non-stationary shock caused by damage.Secondly,a quantitative law that the number of effective eigenvalues of the Hamilton matrix is twice the number of frequency components in the signal during SGMD is found,and the quantitative law is verified by simulation and theoretical derivation.Finally,the trajectory matrix of the pre-whitening signal is constructed and SGMD is performed.According to the quantitative law,the corresponding feature vector is selected to reconstruct the signal.The Hilbert envelope spectrum analysis is performed to extract fault features.Simulation analysis and application examples prove that the proposed method can clearly extract the fault feature of bearings. 展开更多
关键词 cepstrum pre-whitening symplectic geometry mode decomposition EIGENVALUE quantitative law feature extraction
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Cepstrum analysis of seismic source characteristics 被引量:1
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作者 魏富胜 黎明 《Acta Seismologica Sinica(English Edition)》 CSCD 2003年第1期50-58,共9页
This paper introduces the concept of cepstrum. By investigating the difference in source characteristics between earthquakes and explosions the paper infers the manifestation of source difference in various variable d... This paper introduces the concept of cepstrum. By investigating the difference in source characteristics between earthquakes and explosions the paper infers the manifestation of source difference in various variable domains, and seeks for effective means to express such source difference. Extending the approach of source discrimination from time and frequency domain to the cepstrum domain, the paper proposes a method of cepstrum analysis for recognizing the characteristics of seismic sources and establishes criteria for identifying the type of seismic sources. Cepstrum analysis on some recent earthquakes and explosions has been made, and the result shows that the method is quite effective in practice. 展开更多
关键词 cepstrum seismic source DISCRIMINATION
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Parameter recognition for defocus blur image using cepstrum analysis 被引量:1
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作者 周曲 《High Technology Letters》 EI CAS 2008年第3期276-281,共6页
Successful restoration of blurred images depends primarily on the knowledge about the degradationparameter.Defocus blur model in the frequency domain is characterized by concentric rings and the blurradius of the poin... Successful restoration of blurred images depends primarily on the knowledge about the degradationparameter.Defocus blur model in the frequency domain is characterized by concentric rings and the blurradius of the point spread function(PSF)can be identified conveniently in the frequency field for peopleby manual means rather than for computer.This paper introduces a practical method for computer to esti-mate the defocus blur parameter in cepstrum area.Fourier transform plays an intermediate role in the pathto cepstrum domain.We suggest a weighted adjustment operation in the frequency domain and then con-vert it to the cepstrum field to increase the accuracy of recognition. 展开更多
关键词 point spread function (PSF) DEFOCUS BLUR cepstrum
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INDIRECT DETERMINATION METHOD OF DYNAMIC FORCE BY USING CEPSTRUM ANALYSIS
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作者 吴淼 魏任之 《Journal of Coal Science & Engineering(China)》 1996年第2期75-80,共6页
The dynamic load spectrum is one of the most important basis of design and dynamic characteristics analysis of machines. But it is difficult to measure it on many occasions, especially for mining machines, due to thei... The dynamic load spectrum is one of the most important basis of design and dynamic characteristics analysis of machines. But it is difficult to measure it on many occasions, especially for mining machines, due to their bad working circumstances and high cost of measurements. For such situation, the load spectrum has to be obtained by indirect determination methods. A new method to identify the load spectrum, cepstrum analysis method, was presented in this paper. This method can be used to eliminate the filtering influence of transfer function to the response signals so that the load spectrum can be determined indirectly. The experimental and engineering actual examples indicates that this method has the advantages that the calculation is simple and the measurement is easy. 展开更多
关键词 load spectrum indirect determination or identifying cepstrum analysis
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NEW AUTOREGRESSIVE MOVING AVERAGE SPECTRUM ESTIMATION AND CEPSTRUM ALGORITHM
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作者 Zhou Zhaojing,Cheng JieChina Institute of Metrology 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 1997年第2期125-129,共3页
Based on the deduction of the C parameter estimation, a new method to estimate C Parameters from the AR parameters of the ARMA model and auto-related function is proposed , The method reduces the computation complexit... Based on the deduction of the C parameter estimation, a new method to estimate C Parameters from the AR parameters of the ARMA model and auto-related function is proposed , The method reduces the computation complexity of the conventional interative algorithm in MA parameter estimation, thus make the algorithm of ARMA model spectral estimation simpler. On account of this method, a new algo- rithm of cepstrum analysis is put forward . Computer simulation indicates that the proposed cepstrum al- gorithm has the merits of few sidelobes and high resolution . And the algorithm is very useful to the ding- nosis of machinery failure . 展开更多
关键词 SPECTRUM ESTIMATION cepstrum Resolution
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基于语音信号时频特征融合的帕金森病检测方法
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作者 王晨哲 季薇 +1 位作者 郑慧芬 李云 《郑州大学学报(理学版)》 CAS 北大核心 2025年第1期53-60,共8页
发音障碍是帕金森病的早期症状之一。近年来,基于语音信号的帕金森病检测的研究大多采用梅尔刻度下的相关语音特征与深度神经网络模型相结合的方法。然而,现有的模型无法充分关注语音信号的全局时序信息,且梅尔刻度特征在准确表征帕金... 发音障碍是帕金森病的早期症状之一。近年来,基于语音信号的帕金森病检测的研究大多采用梅尔刻度下的相关语音特征与深度神经网络模型相结合的方法。然而,现有的模型无法充分关注语音信号的全局时序信息,且梅尔刻度特征在准确表征帕金森病的病理信息方面效果有限。为此,提出了一种基于语音时频特征融合的帕金森病检测方法。首先,提取语音的梅尔频率倒谱系数,并将其作为模型的输入。接着,在已有的S-vectors模型中引入Conformer编码器模块,以提取语音的时域全局特征。最后,将与帕金森病语音检测相关的频域全局特征嵌入时域特征中进行时频信息融合,以实现帕金森病语音检测。在公开帕金森病语音数据集和自采语音数据集上验证了方法的有效性。 展开更多
关键词 帕金森病 梅尔频率倒谱系数 S-vectors CONFORMER 时频特征融合
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Music/voice separation based on the multi-repeating structure of Mel cepstrum coefficient 被引量:4
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作者 ZHANG Tianqi XU Xin +1 位作者 WU Wangjun LIU Yu 《Chinese Journal of Acoustics》 CSCD 2015年第4期424-435,共12页
For the poor adaptability of the original repeating pattern, an improved music separation method of multi-repeating structure of Mel cepstrum coefficient (MFCC) is proposed. Firstly, the MFCC coefficient matrix (39... For the poor adaptability of the original repeating pattern, an improved music separation method of multi-repeating structure of Mel cepstrum coefficient (MFCC) is proposed. Firstly, the MFCC coefficient matrix (39-dimensional data) of the music signal was extracted. Then the cosine characteristic was applied to the count of similarity matrix of MFCC, and the fragments with consistent similarity are putted together. Next different repeating patterns are built for different groups. Thereby the spectrums of the background music and vocal were separated combined with ideal binary masking (IBM), and the corresponding time domain signals were obtained by inverse Fourier transform. Fnally, the improved method was tested on the music database of different types and length, and the separation results were compared with repeating method of Rafii and the non-negative matrix factorization based on flexible framework method of Ozerov. The experimental results showed that the separation performance of improved method was improved about 3 dB, and the performance of music with melody changed larger was significantly improved. Experiments verified that the improved method was an effective music separation algorithm and more stability. 展开更多
关键词 MFCC Music/voice separation based on the multi-repeating structure of Mel cepstrum coefficient Mel
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Voice conversion using structured Gaussian mixture model in cepstrum eigenspace 被引量:2
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作者 LI Yangchun YU Yibiao 《Chinese Journal of Acoustics》 CSCD 2015年第3期325-336,共12页
A new methodology of voice conversion in cepstrum eigenspace based on structured Gaussian mixture model is proposed for non-parallel corpora without joint training. For each speaker, the cepstrum features of speech ar... A new methodology of voice conversion in cepstrum eigenspace based on structured Gaussian mixture model is proposed for non-parallel corpora without joint training. For each speaker, the cepstrum features of speech are extracted, and mapped to the eigenspace which is formed by eigenvectors of its scatter matrix, thereby the Structured Gaussian Mixture Model in the EigenSpace (SGMM-ES) is trained. The source and target speaker's SGMM-ES are matched based on Acoustic Universal Structure (AUS) principle to achieve spectrum transform function. Experimental results show the speaker identification rate of conversion speech achieves 95.25%, and the value of average cepstrum distortion is 1.25 which is 0.8% and 7.3% higher than the performance of SGMM method respectively. ABX and MOS evaluations indicate the conversion performance is quite close to the traditional method under the parallel corpora condition. The results show the eigenspace based structured Gaussian mixture model for voice conversion under the non-parallel corpora is effective. 展开更多
关键词 LPCC Voice conversion using structured Gaussian mixture model in cepstrum eigenspace ES GMM
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Power Cepstrum and Liftered Spectrum Analysis of Human Pulse Signal
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作者 王炳和 董彦武 +4 位作者 吴胜举 杨颙 相敬林 张效民 王海燕 《Chinese Science Bulletin》 SCIE EI CAS 1994年第8期681-686,共6页
The pulse condition is an important basis for diagnosis and treatment intraditional Chinese medicine. From ancient times, Chinese physicians have been ableto make out the pathological changes of the nine organs by pul... The pulse condition is an important basis for diagnosis and treatment intraditional Chinese medicine. From ancient times, Chinese physicians have been ableto make out the pathological changes of the nine organs by pulse-feeling andpalpation, based on the theory that the pathological mystique lies in the pulsecondition. Chinese physicians have obtained and identified all along the pulsecondition by their finger tips, so there have been inevitably many subjective factors 展开更多
关键词 PULSE SIGNAL POWER cepstrum and liftered SPECTRUM SPECTRAL characteristics.
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Moving target detection in the cepstrum domain for passive coherent location(PCL) radar
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作者 Ji-chuan LI Xiao-de LU +3 位作者 Hui ZHANG Peng-cheng YANG Yu LIU Mao-sheng XIANG 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2015年第9期785-795,共11页
A cepstrum moving target detection (CEPMTD) algorithm based on cepstrum techniques is proposed for passive coherent location (PCL) radar systems. The primary cepstrum techniques are of great success in recognizing... A cepstrum moving target detection (CEPMTD) algorithm based on cepstrum techniques is proposed for passive coherent location (PCL) radar systems. The primary cepstrum techniques are of great success in recognizing the arrival times of static target echoes. To estimate the Doppler frequencies of moving targets, we divide the radar data into a large number of seg- ments, and reformat these segments into a detection matrix. Applying the cepstrum and the Fourier transform to the fast and slow time dimensions respectively, we can obtain the range information and Doppler information of the moving targets. Based on the CEPMTD outlined above, an improved CEPMTD algorithm is proposed to improve the detection performance. Theoretical analyses show that only the target's peak can be coherently added. The performance of the improved CEPMTD is initially vali- dated by simulations, and then by experiments. The simulation results show that the detection performance of the improved CEPMTD algorithm is 13.3 dB better than that of the CEPMTD algorithm and 6.4 dB better than that of the classical detection algorithm based on the radar cross ambiguity function (CAF). The experiment results show that the detection performance of the improved CEPMTD algorithm is 1.63 dB better than that of the radar CAF. 展开更多
关键词 Moving target detection cepstrum techniques Cross ambiguity fimction (CAF) Passive coherent location (PCL)radar
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基于特征融合和B-SVM的鸟鸣声识别算法 被引量:1
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作者 陈晓 曾昭优 《声学技术》 CSCD 北大核心 2024年第1期119-126,共8页
为了实现在野外通过低成本嵌入式系统识别鸟类,提出了基于特征融合和B-SVM的鸟鸣声识别方法。对鸟鸣声信号提取梅尔频率倒谱系数、翻转梅尔频率倒谱系数、短时能量和短时过零率组成特征参数,通过线性判别算法对特征参数进行特征融合。... 为了实现在野外通过低成本嵌入式系统识别鸟类,提出了基于特征融合和B-SVM的鸟鸣声识别方法。对鸟鸣声信号提取梅尔频率倒谱系数、翻转梅尔频率倒谱系数、短时能量和短时过零率组成特征参数,通过线性判别算法对特征参数进行特征融合。利用黑寡妇算法通过测试集对支持向量机模型的核参数和损失值进行优化得到B-SVM模型。利用Xeno-canto鸟鸣声数据集对本文算法进行了测试,结果表明该方法的识别准确率为93.23%。算法维度参数的大小和融合特征维度的高低是影响算法识别效果的重要因素。在相同条件下,文中所提的基于特征融合和B-SVM模型的鸟鸣声识别算法相较于其他特征参数和模型,识别的准确率更高,为野外鸟类识别提供了参考。 展开更多
关键词 鸟鸣声识别 梅尔频率倒谱系数 线性判别算法 黑寡妇优化算法 支持向量机
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梅尔频率倒谱系数在声带息肉手术前后嗓音分析中的价值研究 被引量:1
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作者 刘茉 葛鑫颖 +2 位作者 赵晓畅 郝青青 李祖飞 《中国耳鼻咽喉颅底外科杂志》 CAS CSCD 2024年第2期102-105,共4页
目的 本研究拟通过提取患者嗓音中的梅尔频率倒谱系数(MFCC)指标,探讨其在声带息肉手术前后嗓音分析中的临床价值。方法 回顾性分析于2018年1月—2019年8月行声带息肉手术且术前及术后1个月均行嗓音评估的患者41例,男31例,女10例;平均年... 目的 本研究拟通过提取患者嗓音中的梅尔频率倒谱系数(MFCC)指标,探讨其在声带息肉手术前后嗓音分析中的临床价值。方法 回顾性分析于2018年1月—2019年8月行声带息肉手术且术前及术后1个月均行嗓音评估的患者41例,男31例,女10例;平均年龄(42.9±11.4)岁。另选取无声嘶且无声带病变的正常受试者21例作为基线对照。使用基于Python编程语言的librosa语音处理包进行MFCC特征提取,分别提取每位患者的MFCC均值,MFCC方差与MFCC标准差,使用配对样本t检验比较声带息肉手术前后上述各MFCC特征的差异。结果 声带息肉患者术后MFCC均值1.25±1.01、MFCC方差561.34±154.98及MFCC标准差21.74±4.03比术前MFCC均值6.81±2.05、MFCC方差1 019.66±295.87及MFCC标准差34.37±6.63显著下降,差异具有统计学意义(t=18.596,P=0.000;t=10.338,P=0.000;t=11.852,P=0.000)。声带息肉组患者术后1个月其MFCC均值、MFCC方差及MFCC标准差与正常受试者相比差异均无统计学意义,表明绝大部分声带息肉患者术后嗓音得到良好的恢复。结论 本研究首次探索了MFCC在声带息肉手术前后嗓音分析中的价值,MFCC各特征可作为评估声带息肉术后嗓音恢复的指标。 展开更多
关键词 声带息肉 声嘶 梅尔频率倒谱系数 嗓音分析 手术
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基于模态理论和改进GMM的声发射源识别研究
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作者 杨勇 李晶 +1 位作者 朱作付 邓艾东 《电子器件》 CAS 2024年第1期128-133,共6页
基于模态声发射信号理论,提出了一种利用声学对数倒谱统计参数作为声发射信号特征参数的分析与提取方法。从声发射信号多模态特性出发,提出了一个基于改进高斯混合模型的声发射源信号识别系统。理论分析和实验结果表明,该方法能准确地... 基于模态声发射信号理论,提出了一种利用声学对数倒谱统计参数作为声发射信号特征参数的分析与提取方法。从声发射信号多模态特性出发,提出了一个基于改进高斯混合模型的声发射源信号识别系统。理论分析和实验结果表明,该方法能准确地判断声发射信号源,不仅能够应用于突发型声发射信号的识别,而且可以应用于连续型声发射信号的识别。 展开更多
关键词 声发射信号 倒谱 高斯混合模型 识别
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基于MFCC和GMM的瓷砖空鼓率识别系统及方法
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作者 周浩 梁军汀 卢杰 《无损检测》 CAS 2024年第3期28-32,55,共6页
针对瓷砖因内部空鼓而引起的松动、脱落等质量问题或其他安全隐患问题,研制了一套用于瓷砖空鼓率识别的试验系统。该系统采用梅尔倒谱系数(MFCC)法提取瓷砖敲击声的特征参数,再用高斯混合模型(GMM)法对MFCC特征参数进行分类和识别。试... 针对瓷砖因内部空鼓而引起的松动、脱落等质量问题或其他安全隐患问题,研制了一套用于瓷砖空鼓率识别的试验系统。该系统采用梅尔倒谱系数(MFCC)法提取瓷砖敲击声的特征参数,再用高斯混合模型(GMM)法对MFCC特征参数进行分类和识别。试验结果表明,采用MFCC和GMM相结合的方法,可以对瓷砖空鼓情况进行有效识别,该方法具有良好的应用前景。 展开更多
关键词 声纹识别 梅尔倒谱系数 混合高斯模型
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矿场压裂停泵水击信号滤波效果评价指标研究
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作者 胡晓东 王雅晶 +3 位作者 丘阳 易普康 蒋宗帅 熊壮 《石油钻探技术》 CAS CSCD 北大核心 2024年第6期131-140,共10页
采用水击压力波监测方法进行压裂诊断时,为了准确评价停泵水击压力波信号滤波算法的性能,针对国内某水平井的实测水击信号及其对滤波结果的实际需求,采用倒谱响应分辨率R_(C)和倒频率峰值信噪比R_(QSN)作为水击信号滤波效果的评价指标,... 采用水击压力波监测方法进行压裂诊断时,为了准确评价停泵水击压力波信号滤波算法的性能,针对国内某水平井的实测水击信号及其对滤波结果的实际需求,采用倒谱响应分辨率R_(C)和倒频率峰值信噪比R_(QSN)作为水击信号滤波效果的评价指标,以该指标和滤波效果的同步性为基本依据,根据指标对滤波效果的灵敏性评价滤波指标的可靠程度。研究结果表明,高频水击信号的R_(C)和R_(QSN)与井场信号滤波效果正相关,且呈现出良好的灵敏性,因此能够采用倒谱响应分辨率和倒频率峰值信噪比来评价矿场压裂停泵水击压力波高频信号的滤波效果。研究结果为现场信号特征分析、滤波算法优化及滤波模型现场应用的有效性评估提供了技术途径。 展开更多
关键词 水力压裂诊断 水击压力波监测 水击信号 滤波效果 倒谱响应 倒频率峰值信噪比
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基于倒谱分析的弦乐和打击乐的源分离
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作者 吴礼福 孙芯年 《计算机与数字工程》 2024年第8期2524-2529,共6页
针对音乐中弦乐和打击乐的分离(Harmonic Percussive Sound Separation,HPSS)问题,基于弦乐在时域上跨度长、频域上分布窄,而打击乐在时域上跨度短、频域上分布宽的特点,论文研究了一种倒谱滤波加后处理的分离方法。该方法在倒谱域设计... 针对音乐中弦乐和打击乐的分离(Harmonic Percussive Sound Separation,HPSS)问题,基于弦乐在时域上跨度长、频域上分布窄,而打击乐在时域上跨度短、频域上分布宽的特点,论文研究了一种倒谱滤波加后处理的分离方法。该方法在倒谱域设计滤波器将弦乐和打击乐初步分离后,对打击乐中残留的弦乐部分进行后处理,最后再变换回时域信号。采用音频信号客观评价(Perceptual Evaluation of Audio Quality,PEAQ)算法对分离后的音乐进行评估,结果表明该方法能有效地分离出打击乐和弦乐,同时无需数据驱动类分离方法中大量训练样本的支撑。 展开更多
关键词 弦乐 打击乐 音乐分离 倒谱
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