Filtering Construct of Adaptive Filter Grou Pwith Multi-scale Decomposition

The principle and method of the adaptive filter and the filtering with wavelet transform were analyzed, and the model and method of adaptive filtering with wavelet transforms for the transient signal was established. The separated noise of signal by the multi-scale decomposition of wavelet transforms, was the input signal of adaptive filter, and accordingly the optimal filtering method of signal-noise decomposition was realized. By the adaptive filter grou Pbased on the wavelet transform, the optimal filtering to the multi-noise of signal is achieved at the same time, and the method presented in this paper has the excellent filtering capability. Examples of application demonstrate that this method presented is excellent to realize the optimal estimate to the valuable signal and noise of the transient signal in the same frequency segment.     

Frequency tracking method and simulation for coriolismass flowmter based on a new adaptive notch filter

In order to improve the long-playing frequency tracking ability in the signal processing for coriolis mass flowmeter (CMF) , a new IIR adaptive notch filter (ANF) is developed via steiglitz-mcBride method (SMM) and applied to filter the sensor output signal whose frequency, amplitude and phase are time-varying following the random walk model. The proposed method can detect the signal frequency fleetly and track the frequency variations continuously. The tracking performances of the proposed method and the adaptive lattice notch filter (LANF) method are investigated with computer simulations. Simulations demonstrate the superiority of the proposed method and show it has advantages of fast convergence rate, insensitivity to initial phase variations, and higher long-playing tracking stability and accuracy than LANF method.     

A time-varying signal processing method for Coriolis mass flowmeter

The mass flowrate of Coriolis mass flowmeter in practical application has slow changes with time. To solve the problem, an improved time-varying signal model whose frequency, amplitude and phase are time-varying based on the random walk model is established firstly. A new algorithm of adaptive notch filter with the capability of tracking frequency variation is applied to filter the sensor output signal of Coriolis mass flowmeter and its frequency is calculated next. An adaptive line enhancer based on the mentioned notch filter extracts fundamental frequency signal from noisy data. Then, by short window intercepting, the revised sliding DTFT recursive algorithm is introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and phase difference obtained, the time interval between the two signals is calculated and then the mass flowrate is derived. The simulations and field test results show that the proposed method can not only track the change of frequency and phase, but also ensure the calculation accuracy when measuring small phase difference. The computational load of the algorithm is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.     

Signal Processing Method for Coriolis Mass Flowmeter Based on Lattice Notch Filter and DTFT

A novel signal processing method for Coriolis mass flowmeter is proposed based on time-varying signal model. First, an adaptive lattice notch filter is applied to filter the output signal, whose frequency, amplitude and phase are time-varying based on the random walk model, of Coriolis mass flowmeter to get its frequency and enhanced signal. Then, by short window intercepting, the DTFT algorithm with negative frequency contribution is introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and the phase difference, the time interval between two signals is calculated. Simulation results show that the proposed method is efficient. Furthermore, the computation of algorithms is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.     

Multiresolution Wavelet Transform for Detection of EEG Abnormal Rhythms

The signal of brain activity is a non-stationary random signal including lots of physiology and disease information, which is of important action for doctors to judge pathological changes in brain. So the analysis and process of the EEG signals are always attended. In this paper, the authors take account of the time-frequency localization of wavelet transform and use multiresolution wavelet transform to detect EEG abnormal rhythms. The signals of different scales after EEG signals are transformed by multiresolution wavelet transform not only reflect the frequency information of the signals, namely the more great scale is the lower of the frequency of the signals,but also reflect the time information of the signals, namely EEG state at that time. The test results indicate that the abnormal rhythms of the EEG signals can be detected effectively if right wavelet basis is selected.     

The Application of Narrowband Interference Suppression in Direct Sequence Spread Spectrum

In order to improve the system effect, it is necessary take the technique of digital signal process to suppress interference, because of the finite gain and the narrow-band interference in system of direct sequence spread spectrum. The authors design a new filter structure improving on tunable digital heterodyne adaptive notch filters. This filter can adaptively track the interference frequency and control the bandwidth and depth of notch, which has the excellent agility and utility. The experiment proves this method overcomes limitation of other interference suppressions, hardly weaken the system performances, enhances the stability of the filter system, and can quickly track the interference frequency.     

Temporal-spatial Filtering in the Preprocessing of Clinical EEG Signals

EEG spot-recording for clinical patients in the bed is always advocated due to easing patients and making them comfortable. But EEG signals recorded in the ward exposed to various noisesand interference is less effective in the EEG analysis. Atemporal-spatial filter is designed for noise removing of clinical EEG signals, the first filtering is temporal filtering using band-pass filter, and the second filtering is spatial filtering with ICA-based spatial filter. Experimental results indicate that various noises and interferences, such as power interference, blinking, eyes movements, muscle moments, ECG artifacts, etc., are removed effectively, individually or simultaneously.     

A spread spectrum steganalysis algorithm based on discontinuity detection

A novel audio steganalysis method is proposed.. the audio signal is denoised with wavelet transform. Then, a part of noise signal with different length is intercepted circularly and is used to calculate the cross correlation sequence with the rest of the noise signal. With the wavelet discontinuity detection technique, the feature is extracted from the cross correlation sequence for steganalysis and find out the steg audio. The detection rate is determined by the embedding strength of the secret message other than the embedding capacity. Experimental results show that the more embedding intensity of PN sequence is, the higher the detection rate will be. The detection rate of the algorithm is above 80% when the strength of the PN sequence is about 0.002, which demonstrates that the proposed algorithm has good detection performance.     

Weighted fusion algorithm for frequency estimation of the short signal with the same frequency and length

For high precise frequency estimation of the short sinusoid signal at low signal-to-noise ratio (SNR), a weighted fusion algorithm for frequency estimation of the short signal with the same frequency and length (SFL-Signal) is proposed. The spectrum model of SFL-Signal and the phase compensation matrix with phase coherent and noise cancellation are constructed. Secondly, the SFL-signal spectrum is weight-fused with the phase compensation matrix to obtain the result almost the same as that of the spectrum of the phase-coherent sinusoid signal. Consequently, high frequency estimation precision is obtained with spectral peak searching of the weight-fusion spectrum. Algorithm analysis and simulation results show that, compared with the existing methods,the proposed algorithm works better in term of precision, calculation complexity, noise immunity, and fits for any type of SFL-Signal.     

Study on Nonlinear Dynamical Method for EEG Signal Processing

After studying the meaning of EEG signal processing using systems theory,the basic difficulties of the research on the EEG system and signal analysis are given,showing that it is hard to build model of the EEG system and signal.Hence,we introuduce the method of reconstructing the attractor in state spaces.Through the analysis of some experiments,the meaning of the presented method has been discussed.     

Dynamic Characteristic of Micromachined Arrayed Microphone

Several kinds of microphone developed via silicon Micro Electro Mechanical System (MEMS) processes in recent years are investigated in this paper. The analysis and research of the merits and demerits of them show that: these conventional microphones mainly function as acoustic electric converters; the filtering against noise is implemented by a special filter circuit or a digital filter. Therefore, a design method for silicon micro array filter microphone is presented, where the filtering is achieved while converting signals. The effects of damping, silicon reed number and sensor element pair on dynamic characteristic are discussed; it follows that: Increasing damping can reduce microphone's sensitivity, while increasing silicon reed number can improve the sensitivity curve, furthermore, the implementation of the filter function is simultaneous with acquiring of the noise signal.     

Frequency domain analysis and the application for extracting electroencephalogram signal characteristic waves

A new quantitative analysis method to describe the dynamic variation of electroencephalogram (EEG) signals was proposed. Based on the Fourier transformation, the method is called Fourier multi resolution analysis (FMRA). FMRA decomposes the frequency domain with a binary system and can resolve EEG signals into the basic rhythms of the four waves to study the dynamic characteristics of EEG signal rhythms. FMRA has clear physical meaning, and can obtain more information than wavelet multi resolution analysis does. FMRA can extract perfectly the rhythmic characteristics of EEG signals in the time and frequency domains.     

PD Online Measurement of Transformers with Wide Frequency Band System and the Noise Eliminating Method by Cascaded IIR Lattice Notch Digital Filter

The frequency band of conventional partial discharge (PD) measurement systems is selected just within several ten kilohertz. With the development of computer and digital signal processing techniques, wide frequency band (WFB) measurement systems have been used to detect PD in electrical equipment for its higher sensitivity. Nevertheless, the WFB measurement systems are easy suffered from the interference of strong field electromagnetism noises. A set of PD online monitoring system with frequency band from 50 kHz to 1 megahertz used for transformer is developed, in which pre-processing device and cascaded 2nd order IIR lattice notch digital filter are mainly used to suppress periodic narrow-band interference. With analysis of field monitored signal at a 220 kV substation, it is shown that the monitoring system not only can detect and extract the discharge pulse signal effectively, but also has the powerful capability of suppressing interference.     

A Virtual Wavelet Transform Analyzer for the Signal Analysis Based on the Direct Algorithm

A virtual wavelet transform analyzer for the signal analysis based on the direct algorithm is introduced so that the discrete wavelet transform and continuous wavelet transform is maken to signal in the direct algorithm. The authors first introduce the direct algorithm of the WT, which is numerical algorithm obtained from the original formula of the wavelet transform by directly numericalizing. Then some conclusions are drawn on the direct algorithm. The examples are the sampling principle and technology for the wavelets, the limitation of the scale range of the wavelets and the measures to solve the edge phenomenal in the direct algorithm of the discrete wavelet transform, and some conclusions in the direct algorithm of the continuous wavelet transform. The virtual wavelet transform analyzer for the signal analysis based on the direct algorithm explored based on these studies and combined with virtual instrument technique can make the discrete wavelet transform and continuous wavelet transform to signal with any basic wavelet. It can be applied in studying the property of any basic wavelet and learning the theory on the wavelet transform, and also in making some engineering signal analysis. In the end, the authors give some typical examples for the application of the virtual analyzer. These examples show that the analyzer can be applied in many situations.     

A Practical Method of Eliminating the White Noise of Partial Discharge with Wavelet

The white noise of PD(partial discharge) signal brings great difficult to the PD signal's processing, so eliminating the white noise is a necessary section. There are many methods of eliminating white noise, but none of them are suitable to the PD signal processing. Because PD signal and white noise have different Lipschitz exponents and different wavelet transform features in time-scales, a new eliminating white noise method has been brought forward that has simple operation and meets the timing need of PD signal's processing. After the processing with this method, the PD signal is not distortion and the effect of eliminating white noise is very good. This method can be applied to the processing of PD signal gotten from the site.     

频域滤波的水泥路面图像降噪增强方法

针对在水泥路面裂缝图像识别中刻槽和纵向条带状形成的噪声干扰,提出了一种基于频域滤波的降噪增强方法。首先,分析了这两类噪声的频谱特征,并根据空域图像中刻槽的周期性,推导了频域图像中刻槽谱峰的位置,设计了消除这些谱峰的系列滤波器。根据纵向条带状干扰属于低频成分的特性,设计了抑制低频、增强高频的滤波器,经优化滤波器参数达到消除这类干扰的效果。实验结果表明,该方法能够消除两类噪声干扰,同时,增强了裂缝的对比度,为水泥路面裂缝识别提供了理论基础。     

Method of Time -Frequency Analysis of Engineering Signals Using Wavelet

The method to carry out time frequency analysis of engineering signal using wavelets transform is discussed and the formuli of quantitative relationship between the position & width of time frequency window of wavelet transform and the scale & sampling interval is put forward.     

Application of digital phase-locked loop and filtering technique in PWM rectifier

VHS-ADC high speed digital signal processing platform based on MATLAB and FPGA could be used to build three-phase voltage source rectifier with space voltage vector PWM(SVPWM).The initial phase of coordinate transformation from three phase static coordinate to two phase static coordinate which is called Park transformation and from two phase rotating reference frame to two phase static coordinate is uncertain. There existed noise in acquiring grid voltage and current. Digital phase-locked loop is added to follow the frequency and phase of grid voltage, FIR filter is added to process signal and reduce the interference. External voltage control loop, internal current control loop and the model of coordinate transformation are designed on the VHS-ADC platform. The small power experiment is conducted to verify the stability and feasibility of the control system. The experimental results show that the digital phase-locked loop and FIR digital filter can be applied to three-phase voltage source rectifier.     

Audio blind watermarking scheme combined DWT DCT QR

In order to protect the copyright of digital audio and video in Internet, we propose a novel audio blind watermarking scheme combined discrete wavelets transform, discrete cosine transform, QR decomposition and audio characteristics. In this algorithm, the audio are split into blocks, and each block are decomposed on two dimensional discrete wavelet transform (DWT), then the approximate sub band coefficients are decomposed on discrete cosine transform (DCT), and the first quarter of the DCT coefficients are decomposed on QR decomposition and get a triangle matrix. At last, the watermarking information is embedded into the triangle matrix. The experiments show that the algorithm can get better balance between transparency and robustness of watermark, and it has strong robustness against the common audio signal processing such as additive white Gaussian noise, re sampling, re quantization, low pass filter, MP3 compression and cutting replacement.     

Application of Time-frequency Representations in Study on Heart Sound

Heart sound is non-stationary signal, some of its important characteristics can be obtained by time - frequency analysis method. The criteria of different time-frequency representation concentricity of spectrogram, coverage, MSE and regularity of time envelope axe proposed, the performances of Short-time Fourier transform, Wigner - Ville distribution, continuous wavelet transform, and S transform in study on heart sound are compared based on these criteria , and concrete example of application is given.