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Noise Sensitivity of Teager-Kaiser Energy Operators and Their Ratios  [PDF]
Pradeep Kr. Banerjee,Nirmal B. Chakrabarti
Computer Science , 2015,
Abstract: The Teager-Kaiser energy operator (TKO) belongs to a class of autocorrelators and their linear combination that can track the instantaneous energy of a nonstationary sinusoidal signal source. TKO-based monocomponent AM-FM demodulation algorithms work under the basic assumption that the operator outputs are always positive. In the absence of noise, this is assured for pure sinusoidal inputs and the instantaneous property is also guaranteed. Noise invalidates both of these, particularly under small signal conditions. Post-detection filtering and thresholding are of use to reestablish these at the cost of some time to acquire. Key questions are: (a) how many samples must one use and (b) how much noise power at the detector input can one tolerate. Results of study of the role of delay and the limits imposed by additive Gaussian noise are presented along with the computation of the cumulants and probability density functions of the individual quadratic forms and their ratios.
Teager-Kaiser Energy and Higher-Order Operators in White-Light Interference Microscopy for Surface Shape Measurement  [cached]
Salzenstein Fabien,Montgomery Paul C,Montaner Denis,Boudraa Abdel-Ouahab
EURASIP Journal on Advances in Signal Processing , 2005,
Abstract: In white-light interference microscopy, measurement of surface shape generally requires peak extraction of the fringe function envelope. In this paper the Teager-Kaiser energy and higher-order energy operators are proposed for efficient extraction of the fringe envelope. These energy operators are compared in terms of precision, robustness to noise, and subsampling. Flexible energy operators, depending on order and lag parameters, can be obtained. Results show that smoothing and interpolation of envelope approximation using spline model performs better than Gaussian-based approach.
基于Rife-Vincent窗的高准确度电力谐波相量计算方法  [PDF]
曾博,滕召胜,高云鹏,王一
电工技术学报 , 2009,
Abstract: 非同步采样时,快速傅里叶变换应用于谐波分析容易造成频谱泄露和栅栏效应,影响谐波相量计算的准确度。分析Rife-Vincent窗的旁瓣特性,提出一种基于5项Rife-Vincent(I)窗双谱线插值FFT的谐波相量计算方法。与传统窗函数相比,5项Rife-Vincent(I)窗具有更好的频谱泄漏抑制特性,而双谱线插值算法能够对栅栏效应进行有效修正。仿真实验结果表明,在非同步采样条件下,提出的方法适合于非线性电路谐波相量分析,22次复杂谐波电流信号的频率计算相对误差仅为5.7×10-11%,幅值计算相对误差≤5.3×10-7%,初相位计算相对误差≤3.1×10-6%。
基于Rife-Vincent自卷积窗插值校正的发电机准同期参量测量方法  [PDF]
李永刚,张文静,武玉才,李和明,蒋理,刘剑
电网技术 , 2014, DOI: 10.13335/j.1000-3673.pst.2014.02.015
Abstract: 对准同期参量进行精确快速测量是发电机准同期并列成功的关键。非同步采样时,基于谐波分析理论的准同期参量测量结果会产生较大误差,为此提出了基于Rife-Vincent自卷积窗插值校正的发电机准同期参量测量方法。分析了Rife-Vincent自卷积窗主瓣特性以及自卷积阶数对旁瓣性能的影响,同时给出了基于Rife-Vincent自卷积窗的插值频谱校正方法。通过仿真计算,得到了基波频率波动、谐波影响、噪声影响等不同情况下发电机准同期参量测量结果;同时对电压非稳态情况进行了仿真,分析了误差产生原因。仿真结果表明所提方法性能优越,能有效抑制频谱泄露效应。
A Highly Efficient Generalized Teager-Kaiser-Based Technique for LOS Estimation in WCDMA Mobile Positioning  [cached]
Ridha Hamila,Abdelmonaem Lakhzouri,Elena Simona Lohan,Markku Renfors
EURASIP Journal on Advances in Signal Processing , 2005, DOI: 10.1155/asp.2005.698
Abstract: Line-of-sight signal delay estimation is a crucial element for any mobile positioning system. Estimating correctly the delay of the first arriving path is a challenging topic in severe propagation environments, such as closely spaced multipaths in multiuser scenario. Previous studies showed that there are many linear and nonlinear techniques able to solve closely spaced multipaths when the system is not bandlimited. However, using root raised cosine (RRC) pulse shaping introduces additional errors in the delay estimation process compared to the case with rectangular pulse shaping due to the inherent bandwidth limitation. In this paper, we introduce a novel technique for asynchronous WCDMA multipath delay estimation based on deconvolution with a suitable pulse shape, followed by Teager-Kaiser operator. The deconvolution stage is employed to reduce the effect of the bandlimiting pulse shape.
An improved beam-space MUSIC time delay estimation algorithm based on TK operator
基于Teager-Kaiser算子的改进波束域MUSIC时延估计算法

周非,王路凯,范馨月
重庆邮电大学学报(自然科学版) , 2011,
Abstract: 为了降低波束域多重信号分类(multiple signal classification,MUSIC)算法估计接收信号到达时间(time of arrival,TOA)的计算复杂度,提高算法的抗噪性能,提出一种基于TK算子(Teager-Kaiser operator)的改进算法。利用TK算子对数据瞬时变化敏感的特性,将接收信号与参考信号的相关函数经过TK算子处理,估计出波束域转换矩阵和波束域输出数据,再用MUSIC时延估计算法估计TOA。仿真结果说明,该方法比波束域MUSIC时延估计算法计算量小,并更好地抑制了多径信号噪声影响,高分辨率的估计性能得到了明显改善。
基于Teager-Kaiser算子的改进波束域MUSIC时延估计算法  [PDF]
周非,王路凯,范馨月
重庆邮电大学学报(自然科学版) , 2011,
Abstract: 为了降低波束域多重信号分类(multiplesignalclassification,MUSIC)算法估计接收信号到达时间(timeofarrival,TOA)的计算复杂度,提高算法的抗噪性能,提出一种基于TK算子(Teager-Kaiseroperator)的改进算法。利用TK算子对数据瞬时变化敏感的特性,将接收信号与参考信号的相关函数经过TK算子处理,估计出波束域转换矩阵和波束域输出数据,再用MUSIC时延估计算法估计TOA。仿真结果说明,该方法比波束域MUSIC时延估计算法计算量小,并更好地抑制了多径信号噪声影响,高分辨率的估计性能得到了明显改善。
基于幅值-相角判据的修正Rife正弦波频率估计算法
Modified Rife Algorithm for Frequency Estimation of Sinusoid Wave Based on Amplitude and Phase Criterion
 [PDF]

孙宏军,王小威
- , 2018, DOI: 10.11784/tdxbz201710023
Abstract: 机械工程领域普遍存在正弦信号, 为提高频率估计精度, 提出了一种基于幅值-相角判据的修正Rife算法, 即A-P-Rife算法.针对Rife算法接近两相邻量化频率中心区域时估计精度接近克拉美-罗限(CRLB)的性能特点, 对信号进行FFT变换得到幅值和相角并计算出频移因子.通过设定门限值, 对频移因子进行判断, 满足门限值的信号采用Rife算法进行估计, 不满足门限值的信号则采用相角判据进行估计, 以获得更高的估计精度.仿真结果表明:在频率估计性能上, 所提算法优于原始Rife算法、相角判据算法和M-Rife算法, 其与I-Rife算法性能接近, 但计算量小于I-Rife算法.修正Rife算法可有效提高频率估计精度, 降低误判率并减少计算量, 可应用于工程中的实时频率估计.
Sinusoidal signal is widely encountered in mechanical engineering. A modified algorithm called A-P-Rife algorithm is presented based on the amplitude and phase criterion to improve the estimation accuracy. The frequency estimation accuracy of Rife algorithm could reach Cramer-Rao lower bound(CRLB) when the signal frequency is close to the midpoint of two neighboring discrete frequencies. The amplitude and phase of the signal are obtained by the fast Fourier transform(FFT) in order to calculate the frequency-shifting operator. By setting a threshold value,the frequency-shifting operator is judged to determine which method to employ. If the frequency-shifting operator meets the threshold value,the signal is estimated by Rife algorithm; otherwise,it is estimated by phase criterion. The simulation results indicate that the new algorithm is superior to original Rife algorithm,phase criterion algorithm and M-Rife algorithm in frequency estimation performance,and has less computation than I-Rife algorithm with similar performance. The modified algorithm effectively improves the accuracy of frequency estimation and reduces misjudgment rate. It is proved that the new method can realize real-time frequency estimation of the signal
Gear Fault Detection Based on Teager-Huang Transform  [PDF]
Hui Li,Haiqi Zheng,Liwei Tang
International Journal of Rotating Machinery , 2010, DOI: 10.1155/2010/502064
Abstract: Gear fault detection based on Empirical Mode Decomposition (EMD) and Teager Kaiser Energy Operator (TKEO) technique is presented. This novel method is named as Teager-Huang transform (THT). EMD can adaptively decompose the vibration signal into a series of zero mean Intrinsic Mode Functions (IMFs). TKEO can track the instantaneous amplitude and instantaneous frequency of the Intrinsic Mode Functions at any instant. The experimental results provide effective evidence that Teager-Huang transform has better resolution than that of Hilbert-Huang transform. The Teager-Huang transform can effectively diagnose the fault of the gear, thus providing a viable processing tool for gearbox defect detection and diagnosis. 1. Introduction Gears are important element in a variety of industrial applications such as machine tool and gearboxes [1, 2]. An unexpected failure of the gear may cause significant economic losses. For that reason, fault diagnosis in gears has been the subject of intensive research. Vibration signal analysis has been widely used in the fault detection of rotation machinery. Many methods based on vibration signal analysis have been developed. These methods include power spectrum estimation, fast Fourier transform (FFT), cepstrum analysis, and envelope spectrum analysis, which have been proved to be effective in gear fault detection. However, these methods are based on the assumption of stationarity and linearity of the vibration signal. Therefore, new techniques are needed to analyze vibration signals for fault detection in gear system. Gear fault by their nature are time-localized transient events. To deal with nonstationary and nonlinear signals, time-frequency analysis techniques such as the Short-Time Fourier Transform (STFT) [1], Wavelet Transform (WT) [3–6], and Wigner-Ville distribution (WVD) [7–11] are widely used. The STFT [1] uses sliding windows in time to capture the frequency characteristics as functions of time. Therefore, spectrum is generated at discrete time instants. An inherent drawback with the STFT is the limitation between time and frequency resolutions. A finer frequency resolution can only be achieved at the expense of time resolution and vice versa. Furthermore, this method requires large amounts of computation and storage for display. The Wavelet Transform (WT) [3, 4] has been successfully used in nonstationary vibration signal processing and fault detection. WT is capable of providing both time-domain information and frequency-domain information simultaneously. A very appealing feature of the wavelet analysis is that it
基于双门限判决修正Rife算法的正弦信号频率估计
Frequency Estimation of Sinusoid Based on the Dual-Threshold Decision Modified Rife Algorithm
 [PDF]

崔诵祺,王爱华,汤乐,杨丽丽
- , 2017, DOI: 10.15918/j.tbit1001-0645.2017.03.013
Abstract: 针对正弦信号频率估计复杂度和性能难以兼顾的问题,提出一种基于双门限判决修正Rife算法的频率估计算法。将信号频点划分为3个区域分别采用不同处理方案,具有估计精度高、运算量小的特点,适用于低功耗、低延时等应用场合。仿真结果表明,该方法克服了经典Rife算法在部分频点估计误差大的问题,其频率估计均方根误差距离克拉美罗界仅有0.5dB。与现有其它改进Rife算法相比,该方法在保证估计性能基本不变的前提下大幅降低所需计算量,有利于工程实现。
In order to make a good tradeoff between the complexity and performance for frequency estimation of sinusoid, a frequency estimation algorithm with high estimation accuracy and low computation was proposed based on the dual-threshold decision fixed Rife algorithm. The frequency was divided into three domains with different processing schemes, which would be suitable for low power consumption and low-delay applications. Simulation results show that the method overcomes the inherent flaw of the classic Rife algorithm, and the RMS (root mean square) error for the estimated frequency is only 0.5 dB from the CRB (Cramer-Rao Bound). Compared with other improved Rife algorithms, the new approach can significantly reduce the required computation under the premise of guaranteeing the performance of estimation, be propitious to the engineering.
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