AUTOREGRESSIVE MODEL AND POWER SPECTRUM CHARATERISTICS OF CURRENT SIGNAL IN HIGH FREQUENCY GROUP PULSE MICRO-ELECTROCHEMICAL MACHINING

The identification of the inter-electrode gap size in the high frequency group pulse micro-electrochemical machining （HGPECM） is mainly discussed. The auto-regressive（AR） model of group pulse current flowing across the cathode and the anode are created under different situations with different processing parameters and inter-electrode gap size. The AR model based on the current signals indicates that the order of the AR model is obviously different relating to the different processing conditions and the inter-electrode gap size; Moreover, it is different about the stability of the dynamic system, i.e. the white noise response of the Green＇s function of the dynamic system is diverse. In addition, power spectrum method is used in the analysis of the dynamic time series about the current signals with different inter-electrode gap size, the results show that there exists a strongest power spectrum peak, characteristic power spectrum（CPS）, to the current signals related to the different inter-electrode gap size in the range of 0～5 kHz. Therefore, the CPS of current signals can implement the identification of the inter-electrode gap.

The power spectrum and correlation of flow noise for an axisymmetric body in water

Understanding the physical features of the flow noise for an axisymmetric body is important for improving the performance of a sonar mounted on an underwater platform. Analytical calculation and numerical analysis of the physical features of the flow noise for an axisymmetric body are presented and a simulation scheme for the noise correlation on the hydrophones is given. It is shown that the numerical values of the flow noise coincide well with the analytical values. The main physical features of flow noise are obtained. The flow noises of two different models are compared and a model with a rather optimal fore-body shape is given. The flow noise in horizontal symmetry profile of the axisymmetric body is non-uniform, but it is omni-directional and has little difference in the cross section of the body. The loss of noise diffraction has a great effect on the flow noise from boundary layer transition. Meanwhile, based on the simulation, the noise power level increases with velocity to approximately the fifth power at high frequencies, which is consistent with the experiment data reported in the literature. Furthermore, the flow noise received by the acoustic array has lower correlation at a designed central frequency, which is important for sonar system design.

Earthquake accelerogram simulation with statistical law of evolutionary power spectrum

By using the technique for evolutionary power spectrum proposed by Nakayama and with reference to the Kameda formula, an evolutionary spectrum prediction model for given earthquake magnitude and distance is established based on the 80 near-source acceleration records at rock surface with large magnitude from the ground motion database of western U.S.. Then a new iteration method is developed for generation of random accelerograms non-stationary both in amplitude and frequency which are compatible with target evolutionary spectrum. The phase spectra of those simulated accelerograms are also non-stationary in time and frequency domains since the interaction between amplitude and phase angle has been considered during the generation. Furthermore, the sign of the phase spectrum increment is identified to accelerate the iteration. With the proposed statistical model for predicting evolutionary power spectra and the new method for generating compatible time history, the artificial random earthquake accelerograms non-stationary both in amplitude and frequency for certain magnitude and distance can be provided.

Universal form of the power spectrum of the aero-optical aberration caused by the supersonic turbulent boundary layer

Based on the measurement of one-dimensional （1D） optical path difference （OPD） of the supersonic turbulent bound- ary layer, an analytical form for the power spectrum of the two-dimensional （2D） OPD is obtained with its structure function and under the locally homogeneous isotropic assumption. The universality of this spectrum is argued, and its validity is checked by the comparison with experimental result. The potential applications of this model in theoretical and numerical studies are emphasized. Another contribution of this work is around the application of correlation function to analyzing the statistics of OPD. Based on our results and other results published elsewhere, we show that the OPD is often not stationary, and one should be cautious about using this tool.

BP-Neural-Network-Based Tool Wear Monitoring by Using Wav elet Decomposition of the Power Spectrum

In a drilling process, the power spectrum of the drilling force is related tothe tool wear and is widely applied in the monitoring of tool wear. But the feature extraction andidentification of the power spectrum have always been an unresolved difficult problem. This papersolves it through decomposition of the power spectrum in multilayers using wavelet transform andextraction of the low frequency decomposition coefficient as the envelope information of the powerspectrum. Intelligent identification of the tool wear status is achieved in the drilling processthrough fusing the wavelet decomposition coefficient of the power spectrum by using a BP (BackPropagation) neural network. The experimental results show that the features of the power spectrumcan be extracted efficiently through this method, and the trained neural networks show highidentification precision and the ability of extension.

Effect of focused ultrasound stimulation at different ultrasonic power levels on the local field potential power spectrum

Local field potential(LFP) signals of the rat hippocampus were recorded under noninvasive focused ultrasound stimulation(FUS) with different ultrasonic powers. The LFP mean absolute power was calculated with the Welch algorithm at the delta, theta, alpha, beta, and gamma frequency bands. The experimental results demonstrate that the LFP mean absolute power at different frequency bands increases as the ultrasound power increases.

Texture Feature Extraction Method for Ground Nephogram Based on Contourlet and the Power Spectrum Analysis Algorithm

It is important to extract texture feature from the ground-base cloud image for cloud type automatic detection.In this paper,a new method is presented to capture the contour edge,texture and geometric structure of cloud images by using Contourlet and the power spectrum analysis algorithm.More abundant texture information is extracted.Cloud images can be obtained a multiscale and multidirection decomposition.The coefficient matrix from Contourlet transform of ground nephogram is calculated.The energy,mean and variance characteristics calculated from coefficient matrix are composed of the feature information.The frequency information of the data series from the feature vector values is obtained by the power spectrum analysis.Then Support Vector Machines(SVM)classifier is used to classify according to the frequency information of the trend graph of data series.It is shown that altocumulus and stratus with different texture frequencies can be effectively recognized and further subdivided the types of clouds.

Improved significance testing of wavelet power spectrum near data boundaries as applied to polar research

When one applies the wavelet transform to analyze finite-length time series, discontinuities at the data boundaries will distort its wavelet power spectrum in some regions which are defined as a wavelength-dependent cone of influence （COI）. In the COI, significance tests are unreliable. At the same time, as many time series are short and noisy, the COI is a serious limitation in wavelet analysis of time series. In this paper, we will give a method to reduce boundary effects and discover significant frequencies in the COI. After that, we will apply our method to analyze Greenland winter temperature and Baltic sea ice. The new method makes use of line removal and odd extension of the time series. This causes the derivative of the series to be continuous （unlike the case for other padding methods）. This will give the most reasonable padding methodology if the time series being analyzed has red noise characteristics.

A Combined Numerical-Experimental Study on the Noise Power Spectrum Produced by an Electromagnetic Sensor for Slurry Flow

The signals generated by electromagnetic flow sensors used for slurry fluids are often affected by noise interference produced by interaction with the slurry itself.In this study,the power spectrum characteristics of the signal are studied,and an attempt is made to determine the relationship between the characteristics of the related noise and the velocity and concentration of the slurry fluid.Dedicated experiments are conducted and the related power spectrum curve is obtained processing the signal measured by the sensor with Matlab.Numerical simulations are also carried out in the frame of an Eulerian approach in order get additional insights into the considered problem through comparison with the experimental results.The following conclusions are drawn:(1)The intensity of noise is directly proportional to the number of solid particles colliding with the electrode of the electromagnetic flow sensor per unit time,and to the square of the average velocity of the flow layer near the pipe wall.(2)With an increase in the slurry noise intensity,the power spectrum curve shifts upward in the logarithmic coordinate system(and vice versa).

Research and Implementation of Text Similarity System Based on Power Spectrum Analysis

The paper proposed the research and implement of text similarity system based on power spectrum analysis. It is not difficult to imagine that the signals of brain are closely linked with writing process. So we build text modeling and set pulse signal function to get the power spectrum of the text. The specific detail is getting power spectrum from economic field to build spectral library, and then using the method of power spectrum matching algorithm to judge whether the test text belonged to the economic field. The method made text similarity system finish the function of text intelligent classification efficiently and accurately.

Blind Image Quality Assessment Based on Wavelet Power Spectrum in Perceptual Domain

Blind image quality assessment(BIQA) can assess the perceptual quality of a distorted image without a prior knowledge of its reference image or distortion type. In this paper, a novel BIQA model is developed in wavelet domain. Considering the multi-resolution and band-passing characteristics of discrete wavelet transform(DWT), an improvement over the power spectrum is put forward, i.e., dubbed wavelet power spectrum(WPS)estimation. Then, the concept of directional WPS is applied to simplify the calculation. Moreover, a rotationally symmetric modulation transfer function(MTF) of human visual system(HVS) is integrated as a filter, which makes the metric to be consistent with the human vision perception and more discriminative. Experiments are conducted on the LIVE databases and three other databases, and the results show that the proposed metric is highly correlated with subjective evaluations and it competes well with other state-of-the-art metrics in terms of effectiveness and robustness.

Measurement Quantization Describes History of Universe—Quantum Inflation, Transition to Expansion, CMB Power Spectrum

Developing a comprehensive model of the early universe that describes events and conditions prior to recombination has proved difficult. Using a new approach, we express Heisenberg’s uncertainty principle in terms of measures and counts of those measures to resolve an expression consisting entirely of counts. The description allows us to resolve explicit values for discrete measures. With these values, we present new expressions describing the earliest epoch and the transition event that initiates expansion. We determine the quantity, age, density, and temperature of the cosmic microwave background (CMB). Moreover, we approach the CMB power spectrum anew, describing each mass/energy distribution, its physical significance, its peak temperature, and the effects of relativity. We do not engage in fitting or modification of the existing laws of physics. The approach is classical and correlates both quantum and cosmological phenomena with descriptive expressions that are measurable, verifiable, and falsifiable.

A robust power spectrum split cancellation-based spectrum sensing method for cognitive radio systems

Spectrum sensing is an essential component to realize the cognitive radio, and the requirement for real-time spectrum sensing in the case of lacking prior information, fading channel, and noise uncertainty, indeed poses a major challenge to the classical spectrum sensing algorithms. Based on the stochastic properties of scalar transformation of power spectral density（PSD）, a novel spectrum sensing algorithm, referred to as the power spectral density split cancellation method（PSC）, is proposed in this paper. The PSC makes use of a scalar value as a test statistic, which is the ratio of each subband power to the full band power. Besides, by exploiting the asymptotic normality and independence of Fourier transform,the distribution of the ratio and the mathematical expressions for the probabilities of false alarm and detection in different channel models are derived. Further, the exact closed-form expression of decision threshold is calculated in accordance with Neyman–Pearson criterion. Analytical and simulation results show that the PSC is invulnerable to noise uncertainty,and can achive excellent detection performance without prior knowledge in additive white Gaussian noise and flat slow fading channels. In addition, the PSC benefits from a low computational cost, which can be completed in microseconds.

Classical and modern power spectrum estimation for tune measurement in CSNS RCS

Precise measurement of betatron tune is required for good operating condition of CSNS RCS. The fractional part of betatron tune is important and it can be measured by analyzing the signals of beam position from the appointed BPM. Usually these signals are contaminated during the acquisition process, therefore several power spectrum methods are used to improve the frequency resolution. In this article classical and modern power spectrum methods are used. In order to compare their performance, the results of simulation data and IQT data from J-PARC RCS are discussed, It is shown that modern power spectrum estimation has better performance than the classical ones, though the calculation is more complex.

Effects of Different Extinction for Morphine-CPP on Hippocampal EEG Power Spectrum in Mice

The relationship between hippocampal electroencephalogram(EEG)power spectrum and the extinction of addiction memory was investigated.Forty KM mice(Kunming mice)that had successfully established morphine(MOR)-conditioned place preference(CPP)were divided into four groups:saline-training extinction(SAL-TE),SAL-natural extinction(SAL-NE),MORTE,MOR-NE,for extinction treatment and EEG recording in the dorsal and ventral hippocampus(DH/VH).Results show that the CPP score of MOR-TE significantly decreased and the total,βandγbands power spectrum of MOR-TE was suppressed.Notably,the total power from the VH was more correlated with the extinction method,and the TE total power was always lower than NE in SAL or MOR group.Naloxone enhanced the EEG total power and all bands(DH)orβandγbands(VH)power in the SAL group.However,in the MOR-TE group,onlyβandγbands power in VH increased(P<0.05).The results suggest that TE can promote the extinction of opiate addictive memory more effectively than NE,and the extinction of MOR-CPP may have a stronger correlation with changes of VH-EEG power spectrum.

Blind Carrier Frequency Offset Estimation via Power Spectrum Analysis in MIMO OFDM Systems

As a generalization of orthogonal frequency-division multiplexing （OFDM） systems, multi-input multi-output （MIMO） OFDM systems are very sensitive to carrier frequency offset （CFO）. This paper proposes a blind CFO estimation method based on power spectrum analysis, which has high bandwidth efficiency and is much less complex. This method can be used to estimate the residual CFO, which is less than half of the subcarrier spacing. The method uses a cosine cost function to get a closed-form CFO estimate. Simulation results illustrate that the method is effective for MIMO OFDM systems.

Quality assessment for JPEG images based on difference of power spectrum distribution

No-reference quality assessment aims at designing objective assessment criteria consistent to subjective perceived quality without any knowledge about reference image. This paper proposes a no-reference quality assessment algorithm specific to JPEG images. Blocking artifact in JPEG images is caused by the block based quantization of frequency coefficients, which is equivalent to applying low pass filtering in each block. In view of this idea, the algorithm in this paper was used to realize the quality assessment of JPEG images by quantizing the difference of power spectrum distribution between inner-block and inter-block. The assessment method proposed in this paper owns low algorithm complexity, clear physical meanings, free from learning and training and other advantages. Compared with most presented algorithms, the assessment results of proposed algorithm demonstrate a higher correlation to the subjective perceived quality.

Passive sonar identification (Ⅲ): Feature extraction and pattern plates of double-frequency spectrum as well as average power spectrum

This series of papers deal with vessel recognition. The project is conducted by using fuzzy neural networks and basing on the spectra of vessel radiated-noise. Based on the studies of a large amount of ship radiated-noise data, which has been collected from actual ships on the sea, effectively recognizable features are extracted. Such features include line-spectrum features, stationary and nonstationary spectrum features as well as rhythm features. Finally the categorization are tested by unknown samples on the sea, including 33 surface vessels, 8 underwater vessels in 30 operating conditions. Methods for memorization and classilication are also explored in the project. Paper (Ⅲ) is the thirird in the series. It deals with the extraction method of modulation information in double-frequency power spectrum and the establishment of pattern plate of double-frequency spectrum as well as average power spectrum. To extract features from double-frequency spectrum, the tendency of wave is subtracted from the wave of each channel and the modulation of high frequency is compensated. The modulation degree of lines is shown by relative Value and converted to fuzzy value by fuzzy function. The pattern-plate of double-frequency spectrum memorises stable line and its respective modulation strength. The pattern-plate of average power spectrum memorizes the spectra mean of typical samples and the standard variance

Correlation of EEG power atlas and P300 with depressive episode severity in adolescents hospitalized for the first time

Objective:To investigate the relationship between the changes of electroencephalogram(EEG)power spectrum,P300 latency and amplitude at different frequency bands and the severity of depressive episode in adolescents who were hospitalized for the first time.Methods:A retrospective study was conducted on 126 adolescent patients with depressive episodes who were hospitalized for the first time in the Department of Children and Adolescents of Yunnan Psychiatric Hospital from January 2022 to August 2023.According to Hamilton Depression Rating Scale(HAMD),the patients were divided into three groups:mild depression group(43 cases),moderate depression group(42 cases)and severe depression group(41 cases).The distribution of the 16-lead power spectrum of α,θ,and δ waves in EEG,as well as the latency and amplitude of P300,were compared among the three groups.The association between adolescent depression and its severity was analyzed.Results:(1)The EEG power distribution of the three groups was different in the frequency bands of α,θ and δ(P<0.05).There were differences in the α,θ,and δ frequency bands between mild and moderate as well as severe depressive episodes,and between moderate and severe depressive episodes in the θ and δ frequency bands.(2)P300,N2 latency and P300 amplitude:There were significant differences among the three groups(P<0.05).(3)δFP1,θF3,θC4,P300 latency and N2 latency were positively correlated with the degree of depression;P300 amplitude andα02 were negatively correlated with the degree of depression.(4)The receiver operating characteristic curve(ROC)area of P300 amplitude was 0.932,and the area under the curve ofα02 was 0.776.Conclusion:The combination of resting EEG power and P300 can be used as a biomarker to assess the severity of a depressive episode in adolescents who are hospitalized for the first time and provide a new strategy for treatment.