In our research on the density fluctuations of a supersonic jet we were confronted with a quite difficult problem. In the power spectrum obtained either with a spectrum analyzer, the peaks of the two of the modes that...In our research on the density fluctuations of a supersonic jet we were confronted with a quite difficult problem. In the power spectrum obtained either with a spectrum analyzer, the peaks of the two of the modes that we wanted to identify overlapped. We needed to find a signal processing method that would resolve the two main frequencies. We made a thorough investigation of several methods and thought that parametric periodograms were the appropriate tool. The use of parametric periodograms in signal processing requires constant training. The proper application of this tool depends on the determination of the number of parameters that has to be used to best model a real signal. The methods generally used to determine this number are subjective, depending on trial and error and on the experience of the user. Some of these methods rely on the minimization of the estimated variance of the linear prediction error , as a function of the number of parameters n. In many cases, the graph vs n doesn’t have a minimum, and the methods cannot be used. In this paper, we show that there is a strong relationship between and the frequency resolution . That is, as we modify , we obtain graphs of vs n that present at least one minimum. The spectrum obtained with this optimal number of parameters, always reproduces the frequency information of the original signal. In this paper, we present basically the signal processing of the data obtained in a Rayleigh scattering experiment on a supersonic jet that has also been designed by the authors.展开更多
This paper studies spectral density estimation of a strictly stationary r-vector valued continuous time series including missing observations. The finite Fourier transform is constructed in L-joint segments of observa...This paper studies spectral density estimation of a strictly stationary r-vector valued continuous time series including missing observations. The finite Fourier transform is constructed in L-joint segments of observations. The modified periodogram is defined and smoothed to estimate the spectral density matrix. We explore the properties of the proposed estimator. Asymptotic distribution is discussed.展开更多
Based on the analysis of periodogram, this paper discussed the properties of periodogram of autoregressive integrated moving average process ARIMA（p,1 ,q）, and found that the periodgram of ARIMA（p,1 ,q） process is...Based on the analysis of periodogram, this paper discussed the properties of periodogram of autoregressive integrated moving average process ARIMA（p,1 ,q）, and found that the periodgram of ARIMA（p,1 ,q） process is dominated by the transfer function of the difference operator, which is the same as the result of Crato. The obtained asymptotically properties of the single random walk process was extended to more complicated autoregressive integrated moving average process.展开更多
Based on the maximunl-entropy （ME） principle, a new power spectral estimator for random waves is derived in the form of S（ω）=a/8H^2^-（2π）^（d＋2）exp[-b（2π/ω）^n],1）y solving a variational problem subject ...Based on the maximunl-entropy （ME） principle, a new power spectral estimator for random waves is derived in the form of S（ω）=a/8H^2^-（2π）^（d＋2）exp[-b（2π/ω）^n],1）y solving a variational problem subject to some quite general constraints. This robust method is comprehensive enough to describe the wave spectra even in extreme wave conditions and is superior to periodogranl method that is not suit＇able to process comparatively short or intensively unsteady signals for its tremendous boundary effect and some inherent defects of FKF. Fortunately, the newly derived method for spectral estimation works fairly well, even though the sample data sets are very short and unsteady, and the reliability and efficiency of this spectral estimator have been preliminarily proved.展开更多
Daily return series of Dow Jones Industrial Average Index (DJIA) and Shanghai Conposite Index are investigated using spectral analysis methods. The day of the week effect is found in the frequency domain in both ...Daily return series of Dow Jones Industrial Average Index (DJIA) and Shanghai Conposite Index are investigated using spectral analysis methods. The day of the week effect is found in the frequency domain in both stock markets. Time domain performances of the daily returns are also studied. Although both markets have a clear weekly component in the frequency domain, they show some different behaviors with respect to the day of the week effects.展开更多
Video shot boundary detection is the primary task for content based video management and retrieval system. This paper proposes a shot boundary detection strategy by exploiting the pros of Normalized Periodogram for ef...Video shot boundary detection is the primary task for content based video management and retrieval system. This paper proposes a shot boundary detection strategy by exploiting the pros of Normalized Periodogram for efficiently representing the content of the video. A Normalized Periodogram based distance metric to detect the key frames using shot boundary, namely Distance- Left-Right (D<sub>LR</sub>), is addressed, which is computed on a sliding sub-window basis. The D<sub>LR</sub> sequence is used to detect the suspected shot boundary frames and a transition type detection procedure is adapted to these suspected frames for discriminating the abrupt and gradual transitions. The proposed shot boundary detection methodology yields Precision—95.02%, Recall—93.15% and F1 score—94.07% for cut, Precision—86.57%, Recall—86.67% and F1 score—86.61% for gradual, Precision—90.6%, Recall—90.02% and F1 score—90.3% for overall transitions. Experimental results show that the proposed approach is superior to the recently available shot boundary detection techniques because of its robustness and simplicity, and presents an effective distance metric to detect the shot boundary.展开更多
This study presents an extended version of a single site daily weather generator after Richardson. The model is driven by daily precipitation series derived by a first-order two-state Markov chain and considers the an...This study presents an extended version of a single site daily weather generator after Richardson. The model is driven by daily precipitation series derived by a first-order two-state Markov chain and considers the annual cycle of each meteorological variable. The evaluation of its performance was done by deploying its synthetic time series into the physical based hydrological model BROOK90. The weather generator was applied and tested for data from the Anchor Station at the Tharandt Forest, Germany. Additionally its results were compared to the output of another weather generator with spell-length approach for the precipitation series (LARS-WG). The comparison was distinguished into a meteoro-logical and a hydrological part in terms of extremes, monthly and annual sums and averages. Extreme events could be preserved adequately by both models. Nevertheless a general underestimation of rare events was observed. Natural correlations between vapour pressure and minimum temperature could be conserved as well as annual cycles of the hydro-logical and meteorological regime. But the simulated spectrums of extremes, especially, of precipitation and temperature, are more limited than the observed spectrums. While LARS-WG already finds application in practice, the results show that the data derived from the presented weather generator is as useful and reliable as those from the established model for the simulation of the water balance.展开更多
To estimate the period of a periodic point process from noisy and incomplete observations, the classical periodogram algorithm is modified. The original periodogram algorithm yields an estimate by performing grid sear...To estimate the period of a periodic point process from noisy and incomplete observations, the classical periodogram algorithm is modified. The original periodogram algorithm yields an estimate by performing grid search of the peak of a spectrum, which is equivalent to the periodogram of the periodic point process, thus its performance is found to be sensitive to the chosen grid spacing. This paper derives a novel grid spacing formula, after finding a lower bound of the width of the spectral mainlobe. By employing this formula, the proposed new estimator can determine an appropriate grid spacing adaptively, and is able to yield approximate maximum likelihood estimate （MLE） with a computational complexity of O（n2）. Experimental results prove that the proposed estimator can achieve better trade-off between statistical accuracy and complexity, as compared to existing methods. Simulations also show that the derived grid spacing formula is also applicable to other estimators that operate similarly by grid search.展开更多
We propose a method for estimating mean squared error and bandwidth in the windowedspectral density estimation of a stationary Gaussian process, and also provide a method forestimating the second order derivative of t...We propose a method for estimating mean squared error and bandwidth in the windowedspectral density estimation of a stationary Gaussian process, and also provide a method forestimating the second order derivative of the spectral density function. The asymptotic propertiesand the convergence rates of the estimators are given.展开更多
Preliminary results of the wind velocity estimation using the Maximum Entropy Method (MEM) to MU radar observation data sets are presented. The comparison of the results from the periodogram method and the MEM shows t...Preliminary results of the wind velocity estimation using the Maximum Entropy Method (MEM) to MU radar observation data sets are presented. The comparison of the results from the periodogram method and the MEM shows that the MEM estimation is reliable, and has higher accuracy, resolution and detectability than the estimation from periodogram method. The high accuracy power spectrum obtained by the MEM is very useful to studying the atmospheric turbulence structure. However. the MEM needs the longer computing time for obtaining the high accuracy spectrum. Particularly, the estimation of MEM will bring serious devia- tion at lower signal-to-noise ratio.展开更多
This paper is concerned with the nonparametric spectral density estimation of a stationary Gaussian process. A new estimator of the spectral density is proposed by the bootstrap method. The asymptotic behavior of the ...This paper is concerned with the nonparametric spectral density estimation of a stationary Gaussian process. A new estimator of the spectral density is proposed by the bootstrap method. The asymptotic behavior of the estimate has been studied. The consistency and asymptotic normality of the estimate are given.展开更多
文摘In our research on the density fluctuations of a supersonic jet we were confronted with a quite difficult problem. In the power spectrum obtained either with a spectrum analyzer, the peaks of the two of the modes that we wanted to identify overlapped. We needed to find a signal processing method that would resolve the two main frequencies. We made a thorough investigation of several methods and thought that parametric periodograms were the appropriate tool. The use of parametric periodograms in signal processing requires constant training. The proper application of this tool depends on the determination of the number of parameters that has to be used to best model a real signal. The methods generally used to determine this number are subjective, depending on trial and error and on the experience of the user. Some of these methods rely on the minimization of the estimated variance of the linear prediction error , as a function of the number of parameters n. In many cases, the graph vs n doesn’t have a minimum, and the methods cannot be used. In this paper, we show that there is a strong relationship between and the frequency resolution . That is, as we modify , we obtain graphs of vs n that present at least one minimum. The spectrum obtained with this optimal number of parameters, always reproduces the frequency information of the original signal. In this paper, we present basically the signal processing of the data obtained in a Rayleigh scattering experiment on a supersonic jet that has also been designed by the authors.
文摘This paper studies spectral density estimation of a strictly stationary r-vector valued continuous time series including missing observations. The finite Fourier transform is constructed in L-joint segments of observations. The modified periodogram is defined and smoothed to estimate the spectral density matrix. We explore the properties of the proposed estimator. Asymptotic distribution is discussed.
文摘Based on the analysis of periodogram, this paper discussed the properties of periodogram of autoregressive integrated moving average process ARIMA（p,1 ,q）, and found that the periodgram of ARIMA（p,1 ,q） process is dominated by the transfer function of the difference operator, which is the same as the result of Crato. The obtained asymptotically properties of the single random walk process was extended to more complicated autoregressive integrated moving average process.
基金This research was financially supported by the National Natural Science Foundation of China(Grant No.50479028)a Research Fundfor Doctoral Programs of Higher Education of China(Grant No.20060423009)
文摘Based on the maximunl-entropy （ME） principle, a new power spectral estimator for random waves is derived in the form of S（ω）=a/8H^2^-（2π）^（d＋2）exp[-b（2π/ω）^n],1）y solving a variational problem subject to some quite general constraints. This robust method is comprehensive enough to describe the wave spectra even in extreme wave conditions and is superior to periodogranl method that is not suit＇able to process comparatively short or intensively unsteady signals for its tremendous boundary effect and some inherent defects of FKF. Fortunately, the newly derived method for spectral estimation works fairly well, even though the sample data sets are very short and unsteady, and the reliability and efficiency of this spectral estimator have been preliminarily proved.
文摘Daily return series of Dow Jones Industrial Average Index (DJIA) and Shanghai Conposite Index are investigated using spectral analysis methods. The day of the week effect is found in the frequency domain in both stock markets. Time domain performances of the daily returns are also studied. Although both markets have a clear weekly component in the frequency domain, they show some different behaviors with respect to the day of the week effects.
文摘Video shot boundary detection is the primary task for content based video management and retrieval system. This paper proposes a shot boundary detection strategy by exploiting the pros of Normalized Periodogram for efficiently representing the content of the video. A Normalized Periodogram based distance metric to detect the key frames using shot boundary, namely Distance- Left-Right (D<sub>LR</sub>), is addressed, which is computed on a sliding sub-window basis. The D<sub>LR</sub> sequence is used to detect the suspected shot boundary frames and a transition type detection procedure is adapted to these suspected frames for discriminating the abrupt and gradual transitions. The proposed shot boundary detection methodology yields Precision—95.02%, Recall—93.15% and F1 score—94.07% for cut, Precision—86.57%, Recall—86.67% and F1 score—86.61% for gradual, Precision—90.6%, Recall—90.02% and F1 score—90.3% for overall transitions. Experimental results show that the proposed approach is superior to the recently available shot boundary detection techniques because of its robustness and simplicity, and presents an effective distance metric to detect the shot boundary.
基金supported by the German Academic Exchange Service(DAAD).
文摘This study presents an extended version of a single site daily weather generator after Richardson. The model is driven by daily precipitation series derived by a first-order two-state Markov chain and considers the annual cycle of each meteorological variable. The evaluation of its performance was done by deploying its synthetic time series into the physical based hydrological model BROOK90. The weather generator was applied and tested for data from the Anchor Station at the Tharandt Forest, Germany. Additionally its results were compared to the output of another weather generator with spell-length approach for the precipitation series (LARS-WG). The comparison was distinguished into a meteoro-logical and a hydrological part in terms of extremes, monthly and annual sums and averages. Extreme events could be preserved adequately by both models. Nevertheless a general underestimation of rare events was observed. Natural correlations between vapour pressure and minimum temperature could be conserved as well as annual cycles of the hydro-logical and meteorological regime. But the simulated spectrums of extremes, especially, of precipitation and temperature, are more limited than the observed spectrums. While LARS-WG already finds application in practice, the results show that the data derived from the presented weather generator is as useful and reliable as those from the established model for the simulation of the water balance.
基金supported by the National Natural Science Foundation of China (No. 61002026)
文摘To estimate the period of a periodic point process from noisy and incomplete observations, the classical periodogram algorithm is modified. The original periodogram algorithm yields an estimate by performing grid search of the peak of a spectrum, which is equivalent to the periodogram of the periodic point process, thus its performance is found to be sensitive to the chosen grid spacing. This paper derives a novel grid spacing formula, after finding a lower bound of the width of the spectral mainlobe. By employing this formula, the proposed new estimator can determine an appropriate grid spacing adaptively, and is able to yield approximate maximum likelihood estimate （MLE） with a computational complexity of O（n2）. Experimental results prove that the proposed estimator can achieve better trade-off between statistical accuracy and complexity, as compared to existing methods. Simulations also show that the derived grid spacing formula is also applicable to other estimators that operate similarly by grid search.
文摘We propose a method for estimating mean squared error and bandwidth in the windowedspectral density estimation of a stationary Gaussian process, and also provide a method forestimating the second order derivative of the spectral density function. The asymptotic propertiesand the convergence rates of the estimators are given.
文摘Preliminary results of the wind velocity estimation using the Maximum Entropy Method (MEM) to MU radar observation data sets are presented. The comparison of the results from the periodogram method and the MEM shows that the MEM estimation is reliable, and has higher accuracy, resolution and detectability than the estimation from periodogram method. The high accuracy power spectrum obtained by the MEM is very useful to studying the atmospheric turbulence structure. However. the MEM needs the longer computing time for obtaining the high accuracy spectrum. Particularly, the estimation of MEM will bring serious devia- tion at lower signal-to-noise ratio.
文摘This paper is concerned with the nonparametric spectral density estimation of a stationary Gaussian process. A new estimator of the spectral density is proposed by the bootstrap method. The asymptotic behavior of the estimate has been studied. The consistency and asymptotic normality of the estimate are given.
