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.     

FAST ADAPTIVE FILTERING ( FAF ) FOR THE PROCESS DETECTION CONTROL SYSTEMS

The limitation of LMS adaptive noise cancelling (ANC ) is analyzed here. Based on the discussing of general signal and noise model of process detection control system, a fast adaptive filtering(FAF) is proposed on the basis of modelling the correlativity between the noise and it's correlative noise with the view of large noise. Fast transversal filtering ( FTF ) adaptive, algorithms is used to imitate the correlative modelling. Both simulation and experiments show that the method presented in this paper is suitable for the process detection control system , and it exhibts better results than the LMS noise cancelling method.     

Image edge detection algorithm in fuzzy domain

An image edge detection algorithm in fuzzy domain is proposed, which combines adaptive fuzzy enhancement and multi direction fuzzy morphology to detect the edges of fuzzy image. The adaptive fuzzy enhancement method enhances the fuzzy image within blocks with sliding windows to avoid losses of the real edges resulting from enhancing with single threshold for the whole image and lead strong adaptive ability to image region variance. The multi direction fuzzy mathematical morphology operates on the enhanced fuzzy image with structure elements of multiple different directions to extract the real edges with directionality and restrain non directional noise. Experiments show the algorithm can detect fuzzy image edge effectively with strong antinoise ability.     

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.     

Effective Coefficient Threshold for Complex Wavelet Transform

This paper constructs complex wavelet which used for suppressing white noise in PD,and then analyses some disadvantages of several existing wavelet threshold and presents a method of Effective Wavelet Coefficient(EWC) according to the characteristic of modulus maximum of PD signals.Then it is compared with maximin theory threshold selection and Stein unbiased risk estimate theory threshold selection.The findings suggest that the method of EWC is adaptive,and it can suppress noise completely with small distortion of PD signal.     

Abnormal Noise Test Method of Vehicle Hydraulic Shock Absorber

The work principle and abnormal noise test method of hind vehicle hydraulic shock absorber are analyzed, Based on experiment data and signal character analyse ,a test method is found to distinguish the abnormal noise of rear hydraulic shock absorber. Practical validates that the reliability rate of this test method can be over 98 percents, and it can be satisfied with the request of the factory. At last, the reason of abnormal noise is analyzed and simulated, the reason of different signal attenuation is explained, and the research conclusion is educed.     

Chaotic Synchronization of Discrete Nonlinear Systems on Different Parameters for a Kind of Systems

According to the theory of parameters adaptive control and variable driving, for a kind of discrete nonlinear chaotic systems, a method of chaotic synchronization is presented for different system parameters. In the equation of parameters adaptive control, control coefficients are chaotic signal. Because control coefficients are constant usually for the former parameters adaptive control, so the parameters adaptive control method is very universal, namely the former parameters adaptive control methods are special examples in our control method. Simulation results show that this method is available.     

EEG Signal Denoising Based on Wavelet Transform

The article focuses on the method of noise cancellation for EEG signal. The method of notch filter is discussed. According to the frequency of noise and the principle of notch filter, the design result of the notch filter and the denoised signal are presented. Then, the analysis of EEG signal are proposed based on wavelet transform (WT) and noise cancellation using WT. Wavelet transform is a multi-resolution time-frequency analysis method. It can decompose mixed signal into signals at different frequency bands. The EEG signal is analyzed and denoised using WT, then the results are presented respectively. Comparing the experiment results shows that WT can detect and process noise in the EEG signal effectively.     

The frequency detection model with anti-noise in the autonomous chaotic system

A method of detecting the signal frequency which is disturbed by the noise based on the autonomous chaotic system is proposed. A signal with noise was added to an autonomous chaotic system, and then a negative feedback was imposed to it. The feedback gain was appropriately adjusted, so as to let the noisy system orbit be a limit cycle. The number of times that the orbit went directly through a plane was calculated by loop phase technology, and the vibration frequency was found according to it. The frequency of system is determined by the frequency of the test signal, yet free from noise, so the frequency of the test signal is the vibration frequency of the system. Simulation results further demonstrate the effectiveness of the method.     

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.     

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。     

State of charge estimation of lithium iron phosphate batteriesbased on adaptive Kalman filters

The Kalman filter algorithm can be used to estimate the state of charge (SOC) of power batteries, however, it easily causes divergence due to uncertain of system noise and its estimation performance is affected by model. An adaptive Kalman filter algorithm is adopted to dynamically estimate SOC of lithium iron phosphate batteries for application in electric vehicles. At first, an equivalent circuit model, appropriate for SOC estimation is built after studying battery models. Then some charging and discharging experiments are carried out for parameter identification and the results are verified. At last, the adaptive Kalman filter algorithm is used on this model for on-line SOC estimation under unknown interfering noise. Simulation results show that adaptive Kalman filter method can correct SOC estimation error caused by tiny model error online, and the estimate accuracy is higher than Kalman filter method. Adaptive Kalman filter algorithm can also correct the initial error. Full-cycle test in electric vehicles proves that the algorithm is appropriate for SOC estimation of lithium iron phosphate battery.     

Application of Wavelet Denoising in Partial Discharge Online Monitoring of Transformer

Because of the strong interferences, such as discrete spectrum interferences (DSI), white noise and pulse-shaped interferences, it is still a difficult work to extract the partial discharge (PD) signal for transformer online monitoring techniques. Through deeply study on the automatic selection of threshold value and mother wavelet, the wavelet-based de-noising method for partial discharge signals is proposed. The analyzing results on simulation signal and field-measured signal indicate that the proposed method is fit for de-noising white noise but for DSI the comparably worse de-noising results is acquired. Hence it is predicted that good de-noising results will be achieved with the wavelet-based de-noising method combined with digital filtering method fitting for de-noising DSI.     

Image denoising based on adaptive graph regularization

Adaptive regularization can select different parameters based on the features of local areas in an image, which can differentiate the edges and noise in an image flexibly. An adaptive graph regularization is proposed based on graph spectral theory and adaptive regularization, which uses the Non local means to generate the weighting function of graph. The adaptive graph regularization equation is used to filter the noisy image. Simulation results show that the proposed method can effectively remove the noise and is superior to other graph theory based partial differential equation methods.     

Application of Wavelet & Multi-Resolution Analysis to Detection of the Time of PN Code Acquisition

In the field of CDMA system, DS-SS technology has been used widely. Thereby, a great deal research on acquisition method of PN code is based on DS-SS. In the traditional way, the power detection method of judgment is used widely. Based on the characteristic of PN code acquired signal (namely BPSK signal or QPSK signal) and characteristic of un acquired signal (namely white Gaussian noise), this paper introduces the wavelet detection method of PN code acquisition time. Meanwhile, the performance of wavelet threshold is also studied. In the end, the statistics of parameters in this detection method is made. The result indicates that the wavelet & multi resolution has practical value in the signal processing.     

Anti interference Study of Differential Coil for Measuring Fast High Current Impulse

The problem that the internal electrical interference is nuavoidable for differential coil in measuring fast high current impulse is discussed.The shielded differential coil which has a chink in the middle of its shield can reduce this interference,and that the signal to noise ratio of the differential measurement is 27 shows the anti interference efficiency of this coil.Furthermore,the double differential coil which use the differential balanced technique to resisting the interference make the signal to noise ratio of the differential mearsurement be 57.     

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.     

珍稀植物细枝岩黄耆自适应群团抽样的比较研究

对于稀少、群团状总体的调查,自适应群团抽样（adaptive cluster sampling,简称ACS）被认为是一种有效的抽样方法。针对中国西部森林植被的集聚、稀少的分布特征,以乌兰布和沙漠边缘地区细枝岩黄耆株数密度为研究对象,进行6种抽样方法（简单放回随机抽样、简单不放回随机抽样、最初样本放回基于修正Hansen-Hurwitz估计量的ACS、最初样本不放回基于修正Hansen-Hurwitz估计量的ACS、最初样本放回基于修正Horvitz-Thompson估计量的ACS和最初样本不放回基于修正Horvitz-Thompson估计量的ACS）的重复抽样模拟试验,并对模拟试验的结果进行了比较和分析,指出最初样本不放回基于Horvitz-Thompson估计量的自适应群团抽样的效果最佳,其均值估计相对误差为0.037%,均值方差估计为0.03571。研究结果有助于提高稀少、群团状森林资源的清查的精度和效率。     

A blind adaptive reduced-rank receiver for ultra-wideband communication systems

A low-complexity blind adaptive receiver for ultra-wideband (UWB) systems in the presence of both multiple access interference (MAI) and inter symbol interference (ISI) is proposed, which is composed of two stages. In the first stage, a reduced-rank algorithm based on the multi-stage Wiener filter (MSWF) is considered to suppress the MAI and extract multi-path components. Channel estimation using the projection approximation subspace tracking with deflation (PASTd) algorithm and multi-path combining are then performed to further enhance the signal to interference plus noise ratio (SINR) of the desired user in the second stage. The simulation results show that the proposed receiver exhibits reasonably good bit error ratio (BER) performance compared with those of matched filter, conventional Rake receiver, decorrelating Rake receiver and adaptive receiver based on constant modulus algorithm (CMA). Moreover, it has faster convergence speed and less complexity.     

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.