Adaptive Bistable Stochastic Resonance Based Weak Signal Reception in Additive Laplacian Noise

Weak signal reception is a very important and challenging problem for communication systems especially in the presence of non-Gaussian noise,and in which case the performance of optimal linear correlated receiver degrades dramatically.Aiming at this,a novel uncorrelated reception scheme based on adaptive bistable stochastic resonance(ABSR)for a weak signal in additive Laplacian noise is investigated.By analyzing the key issue that the quantitative cooperative resonance matching relationship between the characteristics of the noisy signal and the nonlinear bistable system,an analytical expression of the bistable system parameters is derived.On this basis,by means of bistable system parameters self-adaptive adjustment,the counterintuitive stochastic resonance(SR)phenomenon can be easily generated at which the random noise is changed into a benefit to assist signal transmission.Finally,it is demonstrated that approximately 8dB bit error ratio(BER)performance improvement for the ABSR-based uncorrelated receiver when compared with the traditional uncorrelated receiver at low signal to noise ratio(SNR)conditions varying from-30dB to-5dB.

An algorithm to remove noise from locomotive bearing vibration signal based on self-adaptive EEMD filter

An improved ensemble empirical mode decomposition(EEMD) algorithm is described in this work, in which the sifting and ensemble number are self-adaptive. In particular, the new algorithm can effectively avoid the mode mixing problem. The algorithm has been validated with a simulation signal and locomotive bearing vibration signal. The results show that the proposed self-adaptive EEMD algorithm has a better filtering performance compared with the conventional EEMD. The filter results further show that the feature of the signal can be distinguished clearly with the proposed algorithm, which implies that the fault characteristics of the locomotive bearing can be detected successfully.

Modeling random telegraph signal noise in CMOS image sensor under low light based on binomial distribution

The random telegraph signal noise in the pixel source follower MOSFET is the principle component of the noise in the CMOS image sensor under low light. In this paper, the physical and statistical model of the random telegraph signal noise in the pixel source follower based on the binomial distribution is set up. The number of electrons captured or released by the oxide traps in the unit time is described as the random variables which obey the binomial distribution. As a result,the output states and the corresponding probabilities of the first and the second samples of the correlated double sampling circuit are acquired. The standard deviation of the output states after the correlated double sampling circuit can be obtained accordingly. In the simulation section, one hundred thousand samples of the source follower MOSFET have been simulated,and the simulation results show that the proposed model has the similar statistical characteristics with the existing models under the effect of the channel length and the density of the oxide trap. Moreover, the noise histogram of the proposed model has been evaluated at different environmental temperatures.

Joint DOA and polarization estimation for unequal power sources based on reconstructed noise subspace

In most literature about joint direction of arrival（DOA） and polarization estimation, the case that sources possess different power levels is seldom discussed. However, this case exists widely in practical applications, especially in passive radar systems. In this paper, we propose a joint DOA and polarization estimation method for unequal power sources based on the reconstructed noise subspace. The invariance property of noise subspace（IPNS） to power of sources has been proved an effective method to estimate DOA of unequal power sources. We develop the IPNS method for joint DOA and polarization estimation based on a dual polarized array. Moreover, we propose an improved IPNS method based on the reconstructed noise subspace, which has higher resolution probability than the IPNS method. It is theoretically proved that the IPNS to power of sources is still valid when the eigenvalues of the noise subspace are changed artificially. Simulation results show that the resolution probability of the proposed method is enhanced compared with the methods based on the IPNS and the polarimetric multiple signal classification（MUSIC） method. Meanwhile, the proposed method has approximately the same estimation accuracy as the IPNS method for the weak source.

Effects of signal modulation and coloured cross-correlation of coloured noises on the diffusion of a harmonic oscillator

The diffusion in a harmonic oscillator driven by coloured noises ξ（t） and η（t） with coloured cross-correlation in which one of the noises is modulated by a biased periodic signal is investigated. The exact expression of diffusion coefficient d as a function of noise parameter, signal parameter, and oscillator frequency is derived. The findings in this paper are as follows. 1） The curves of d versus noise intensity D and d versus noises cross-correlation time z3 exist as two different phases. The transition between the two phases arises from the change of the cross-correlation coefficient A of the two Ornstein-Uhlenbeck （O-U） noises. 2） Changing the value of T3, the curves of d versus Q, the intensity of colored noise that is modulated by the signal, can transform from a phase having a minimum to a monotonic phase. 3） Changing the value of signal amplitude A, d versus Q curves can transform from a phase having a minimum to a monotonic phase. The above-mentioned results demonstrate that a like noise-induced transition appears in the model.

Occurring Mechanism and Restraining Method Research of Numerical Noise Signal in Penetration Simulation

In hard target penetration simulation, the existing researches of the convergence of results are mainly concentrating in the corresponding relationship between penetration depth and mesh scales. However, the influence of the mesh difference on the penetration resistance and acceleration signals are seldom refer to. This paper presents the occurring mechanism and restraining method of numerical noise signal in penetration simulation. First, the concept of the noise signal izs proposed. By taking a 3D penetration simulation as example, the influence of the noise signal on the penetration resistance in different mesh scales and impact velocity is studied. To ensure the convergence of the computational results, the grid scale of the target is encrypted to 1：1：8. In addition, modem spectrum analysis method is introduced to further analyze the penetration resistance signal. The research results presented is useful to improve the computational accuracy of high speed projectile penetration simulation, and provide important reference for carrying out structural design and optimization of fuze system.

The Ultimate Noise Limit for Hall Plates in Voltage, Current, and Hybrid Operating Modes

If Hall plates are used as magnetic field sensors they are usually powered up by a current source connected to a pair of non-neighboring contacts. The output voltage is tapped at another pair of non-neighboring contacts. In this paper we study more general operating conditions of Hall plates with an arbitrary number of contacts. In such hybrid operating modes current sources are connected to a first set of contacts and voltage sources to a second set of contacts. Output voltages are tapped at the first set of contacts and output currents are measured at the second set of contacts. All these output signals are multiplied by coefficients and added up. The purpose of this work is to figure out which operating mode and which Hall plate achieve maximum signal at minimum thermal noise and power dissipation. To this end we develop a theory, which gives the ratio of signal over noise and power as a function of the resistance matrix of Hall plates, of the supply voltages and currents, and of the coefficients. Optimization is done analytically in closed form and numerically for specific examples. The results are: 1) all operating modes have identical noise performance if their parameters are optimized;2) for any Hall plate one can measure its resistance matrix and insert its values into our formulae to obtain the optimum supply currents and coefficients for optimum noise performance.

A Robust Asynchrophasor in PMU Using Second-Order Kalman Filter

Phasor Measurement Units(PMUs)provide Global Positioning System(GPS)time-stamped synchronized measurements of voltage and current with the phase angle of the system at certain points along with the grid system.Those synchronized data measurements are extracted in the form of amplitude and phase from various locations of the power grid to monitor and control the power system condition.A PMU device is a crucial part of the power equipment in terms of the cost and operative point of view.However,such ongoing development and improvement to PMUs’principal work are essential to the network operators to enhance the grid quality and the operating expenses.This paper introduces a proposed method that led to lowcost and less complex techniques to optimize the performance of PMU using Second-Order Kalman Filter.It is based on the Asyncrhophasor technique resulting in a phase error minimization when receiving the signal from an access point or from the main access point.The MATLAB model has been created to implement the proposed method in the presence of Gaussian and non-Gaussian.The results have shown the proposed method which is Second-Order Kalman Filter outperforms the existing model.The results were tested usingMean Square Error(MSE).The proposed Second-Order Kalman Filter method has been replaced with a synchronization unit into thePMUstructure to clarify the significance of the proposed new PMU.

An Enhanced Graphical Authentication Scheme Using Multiple-Image Steganography

Most remote systems require user authentication to access resources.Text-based passwords are still widely used as a standard method of user authentication.Although conventional text-based passwords are rather hard to remember,users often write their passwords down in order to compromise security.One of the most complex challenges users may face is posting sensitive data on external data centers that are accessible to others and do not be controlled directly by users.Graphical user authentication methods have recently been proposed to verify the user identity.However,the fundamental limitation of a graphi-cal password is that it must have a colorful and rich image to provide an adequate password space to maintain security,and when the user clicks and inputs a pass-word between two possible grids,the fault tolerance is adjusted to avoid this situation.This paper proposes an enhanced graphical authentication scheme,which comprises benefits over both recognition and recall-based graphical techniques besides image steganography.The combination of graphical authentication and steganography technologies reduces the amount of sensitive data shared between users and service providers and improves the security of user accounts.To evaluate the effectiveness of the proposed scheme,peak signal-to-noise ratio and mean squared error parameters have been used.

Regulatory Genes Through Robust-SNR for Binary Classification Within Functional Genomics Experiments

The current study proposes a novel technique for feature selection by inculcating robustness in the conventional Signal to noise Ratio(SNR).The proposed method utilizes the robust measures of location i.e.,the“Median”as well as the measures of variation i.e.,“Median absolute deviation(MAD)and Interquartile range(IQR)”in the SNR.By this way,two independent robust signal-to-noise ratios have been proposed.The proposed method selects the most informative genes/features by combining the minimum subset of genes or features obtained via the greedy search approach with top-ranked genes selected through the robust signal-to-noise ratio(RSNR).The results obtained via the proposed method are compared with wellknown gene/feature selection methods on the basis of performance metric i.e.,classification error rate.A total of 5 gene expression datasets have been used in this study.Different subsets of informative genes are selected by the proposed and all the other methods included in the study,and their efficacy in terms of classification is investigated by using the classifier models such as support vector machine(SVM),Random forest(RF)and k-nearest neighbors(k-NN).The results of the analysis reveal that the proposed method(RSNR)produces minimum error rates than all the other competing feature selection methods in majority of the cases.For further assessment of the method,a detailed simulation study is also conducted.

毒物分析中四极杆质谱仪扫描速率对灵敏度影响研究

To find out the effect of scan rate on sensitivity in quadrupole mass spectrometer,DDV and 11 common hypnotic drugs were chosen for GC-MS analysis.Different scan time and dwell time was used separately for full scan mode and SIM.Then charasteristic ions were extracted to calculate signal to noise values.

Comparison of simultaneous signals obtained from a dual-field-of-view lidar and its application to noise reduction based on empirical mode decomposition

Although the empirical mode decomposition （EMD） method is an effective tool for noise reduction in lidar signals, evaluating the effectiveness of the denoising method is difficult. A dual-field-of-view lidar for observing atmospheric aerosols is described. The backscattering signals obtained from two channels have different signal-to-noise ratios （SNRs）. The performance of noise reduction can be investigated by comparing the high SNR signal and the denoised low SNR signal without a simulation experiment. With this approach, the signal and noise are extracted to one intrinsic mode function （IMF） by the EMD- based denoising; thus, the threshold method is applied to the IMFs. Experimental results show that the improved threshold method can effectively perform noise reduction while preserving useful sudden-change information.

An Algorithm for Ship Wake Detection from the SAR Images Using the Radon Transform and Morphological Image Processing

Using the Radon transform and morphological image processing, an algorithm for ship's wake detection in the SAR (synthetic aperture radar) image is developed. Being manipulated in the Radon space to invert the gray-level and binary images, the linear texture of ship wake in oceanic clutter can be well detected. It has been applied to the automatic detection of a moving ship from the SEASAT SAR image. The results show that this algorithm is well robust in a strong noisy background and is not very sensitive to the threshold parameter and the working window size.

Micro-Doppler feature extraction of micro-rotor UAV under the background of low SNR

Micro-Doppler feature extraction of unmanned aerial vehicles(UAVs)is important for their identification and classification.Noise and the motion state of the UAV are the main factors that may affect feature extraction and estimation precision of the micro-motion parameters.The spectrum of UAV echoes is reconstructed to strengthen the micro-motion feature and reduce the influence of the noise on the condition of low signal to noise ratio(SNR).Then considering the rotor rate variance of UAV in the complex motion state,the cepstrum method is improved to extract the rotation rate of the UAV,and the blade length can be intensively estimated.The experiment results for the simulation data and measured data show that the reconstruction of the spectrum for the UAV echoes is helpful and the relative mean square root error of the rotating speed and blade length estimated by the proposed method can be improved.However,the computation complexity is higher and the heavier computation burden is required.

An effective fractal image compression algorithm based on plane fitting

A new method using plane fitting to decide whether a domain block is similar enough to a given range block is proposed in this paper. First, three coefficients are computed for describing each range and domain block. Then, the best-matched one for every range block is obtained by analysing the relation between their coefficients. Experimental results show that the proposed method can shorten encoding time markedly, while the retrieved image quality is still acceptable. In the decoding step, a kind of simple line fitting on block boundaries is used to reduce blocking effects. At the same time, the proposed method can also achieve a high compression ratio.

STAP中采样支持问题研究(英文)

In the airborne radar space-time adaptive processing (STAP), the interference covariance matrix must be estimated from the IID samples which are always limited in practice. Aimed at this problem, this paper studies the combination of the forward-backward averaging (FB), diagonal loading (DL) and the reduced-rank processing to reduce the required sample number as much as possible. Through analysis and simulations, it is demonstrated that by using proper reduced-rank processing, combined with FB and DL, the required sample number can be largely reduced to even 3-5 samples.

Highly sensitive detection of Rydberg atoms with fluorescence loss spectrum in cold atoms

Fluorescence loss spectrum for detecting cold Rydberg atoms with high sensitivity has been obtained based on lock-in detection of fluorescence of 6 P3/2 state when cooling lasers of the magneto-optical trap are modulated.The experiment results show that the signal to noise ratio has been improved by 32.64 dB when the modulation depth(converted to laser frequency)and frequency are optimized to 4 MHz and 6 kHz,respectively.This technique enables us to perform a highly sensitive non-destructive detection of Rydberg atoms.

Performance Analysis of Two CFAR Detectors in Clutter Edge Situation

This paper studies the performance of the GOSGO and GOSSO CFAR detectors [1] in clutter edge situation. The authors derive the analytic expressions of the false alarm probabilities in that situation, analyze their performances against clutter edge, and compare them with the OS, CA, GO and SO detectors. The results show that GOSGO possesses better performance than GO for countering clutter, but the performance of GOSSO is very unideal.

A Novel Peak-to-Average Power Ratio Reduction Scheme via Tone Reservation in OFDM Systems

In this paper, a novel signal-to-clipping noise ratio and least squares approximation tone reservation scheme(SCR-LSA TR) is proposed to reduce the peak-to-average power ratio for orthogonal frequency division multiplexing systems. During the SCR procedure, only the element with the maximal amplitude is picked for processing, which not only decreases the algorithm complexity, but also helps to overcome the BER deterioration. With the LSA method, the amplitude of the peak-cancelling signals can approximate to that of the original clipping noise as much as possible. Through the combination of the optimization factor in the LSA method, the classic SCR method can achieve better PAPR reduction with faster convergence. Simulation results show that the proposed SCR-LSA TR scheme has less in-band distortion and smaller out-of-band spectral radiation. The BER of the proposed scheme shows a better performance especially under the 16-QAM over the additive white Gaussian noise channel.

Parameters Optimization of Laser-Induced Breakdown Spectroscopy Experimental Setup for the Case with Beam Expander

Improvement of measurement precision and repeatability is one of the issues currently faced by the laser-induced breakdown spectroscopy （LIBS） technique, which is expected to be capable of precise and accurate quantitative analysis. It was found that there was great potential to improve the signal quality and repeatability by reducing the laser beam divergence angle using a suitable beam expander （BE）. In the present work, the influences of several experimental parameters for the case with BE are studied in order to optimize the analytical performances： the signal to noise ratio （SNR） and the relative standard deviation （RSD）. We demonstrate that by selecting the optimal experimental parameters, the BE-included LIBS setup can give higher SNR and lower RSD values of the line intensity normalized by the whole spectrum area. For validation purposes, support vector machine （SVM） regression combined with principal component analysis （PCA） was used to establish a calibration model to realize the quantitative analysis of the ash content. Good agreement has been found between the laboratory measurement results from the LIBS method and those from the traditional method. The measurement accuracy presented here for ash content analysis is estimated to be 0.31%, while the average relative error is 2.36%.