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.

Noise reduction and signal to noise ratio improvement in magneto-optical polarization rotation measurement

The measurement of an extremely small magneto-optical polarization rotation angle with high sensitivity is integral to many scientific and technological applications. In this Letter, we have presented a technique based on Faraday modulation combined with the optical differential method to measure an extremely small polari- zation rotation angle with high sensitivity. The theoretical and experimental results show that common mode noise is reduced appreciably and signal to noise ratio is enhanced. The effectiveness of this technique has been demonstrated by measuring the Verdet constant of terbium gallium garnet glass and measuring the small polari- zation rotation angle. A sensitivity of enhancement of one order of magnitude has been achieved using differ- ential detection based on Faraday modulation.

Simultaneous optical signal to noise ratio and symbol rate estimation with blind chromatic dispersion compensation for auxiliary amplitude modulation optical signals

Based on the peak to valley ratio（PTVR） of the average magnitude difference function（AMDF）, we present a novel optical signal to noise ratio（OSNR） and symbol rate（SR） estimation method for commonly used auxiliary amplitude modulations（AAMs）. Moreover, it is demonstrated that the influence of chromatic dispersion（CD）on the method can be mitigated by maximizing the PTVR of the AMDF with additional tunable dispersion compensators. The results of simulations show that the OSNR estimation error can be kept within 0.8 dB in the wide OSNR range of（12, 32） dB, while the SR estimation error is below 0.079% for four widely used10 Gsymbol/s AAM signals.

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.

Fourier Spectrometer based on Wide-range and Phase-locked Michelson Interferometer with Femtosecond Laser Excitation

A wide-range and phase-locked Michelson interferometer technique is described. This technique combined with femtosecond laser is used to measure the spectrum of the rare-earth ion Nd：YVO4, which presents very high signal to noise ratio of interferometric intensity output and higher spectral resolution than traditional grating spectrophotometer.

The most homogeneous dip-scanning method using edgepreserving smoothing for seismic noise attenuation

Highlighting and analyzing the geological features of faults and fractures in seismic data is particularly important for hydrocarbon exploration and exploitation since they are often essential for finding and delineating reservoirs. We apply edge-preserving smoothing （EPS） to seismic processing and propose a most homogeneous dip-scanning method. The method preserves the geological features, eliminate random noise efficiently, obtain dip information, and improve the accuracy of identifying the oil and gas traps.

Influence of the nonlinear propagation effect on the optical signal-to-noise ratio of 400G optical fiber communication systems

The influence of the nonlinear propagation effect on three 400 Gb/s/ch （400G） optical fiber communication systems with typical modulation formats, dual-carrier 16-quadrature amplitude modulation （16QAM）, single-carrier 16QAM （single-16QAM）, and four-carrier quadrature phase-shift keying, are investigated. The received optical signal-to-noise ratio （OSNR）, affected by the nonlinear interference noise together with the amplified spontaneous emission noise, are compared with three 400G systems and a standard 100 Gb/s/ch system by numerical simulations. Both single channel and multichannel cases are considered. Single-16QAM is found to have the best OSNR among those modulation formats.

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.

Denoising Letter Images from Scanned Invoices Using Stacked Autoencoders

Invoice document digitization is crucial for efficient management in industries.The scanned invoice image is often noisy due to various reasons.This affects the OCR(optical character recognition)detection accuracy.In this paper,letter data obtained from images of invoices are denoised using a modified autoencoder based deep learning method.A stacked denoising autoencoder(SDAE)is implemented with two hidden layers each in encoder network and decoder network.In order to capture the most salient features of training samples,a undercomplete autoencoder is designed with non-linear encoder and decoder function.This autoencoder is regularized for denoising application using a combined loss function which considers both mean square error and binary cross entropy.A dataset consisting of 59,119 letter images,which contains both English alphabets(upper and lower case)and numbers(0 to 9)is prepared from many scanned invoices images and windows true type(.ttf)files,are used for training the neural network.Performance is analyzed in terms of Signal to Noise Ratio(SNR),Peak Signal to Noise Ratio(PSNR),Structural Similarity Index(SSIM)and Universal Image Quality Index(UQI)and compared with other filtering techniques like Nonlocal Means filter,Anisotropic diffusion filter,Gaussian filters and Mean filters.Denoising performance of proposed SDAE is compared with existing SDAE with single loss function in terms of SNR and PSNR values.Results show the superior performance of proposed SDAE method.

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.

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.

RESEARCH ON PERFORMANCE INFLUENCE OF DIRECT-PATH SIGNAL FOR DVB-S BASED PASSIVE RADAR

Passive radar detects moving targets by Cross Ambiguity Function (CAF), which is based on the cross correlation process of the direct-path signal in reference channel and echo signal in receive channel. Thus, the performance of direct-path signal is important to system performance for this type of radar. While the Signal to Noise Ratio (SNR) of direct-path signal is low, it will deteriorate the detection performance. In this paper, how SNR of direct-path signal induces degradation on the SNR of CAF, and how the integration gain affects by integration time are analyzed, both with theoretical analysis and numerical simulation, which are valuable for the R&D of passive radar.

Numerical analysis of Raman amplification and optical signal-to-noise ratio in a photonic crystal fiber

A numerical design on the triangular photonic crystal fiber （PCF） based backward multi-pump Raman amplifier is presented. It is demonstrated that high flat Raman gain can be reached based on PCF. Influences of different geometric parameters and germanium doping concentrations on the Raman net gain, amplified spontaneous emission （ASE） noise and double Rayleigh backscattering （DRBS） of the signal have been analyzed. For optimizing crystal fiber Raman amplifier （FRA）, there is tradeoff between the geometric parameter and germanium doping concentration of triangular PCF. The results show that PCF is an appropriate candidate for high gain Raman amplifiers.

Signal recovery method based on co-prime array

A signal waveform recovery method based on the co-prime array is investigated to extract the waveform of the desired signal from spatial interferences in narrowband scenarios. The direction of arrivals (DOAs) of the desired signal and interference signals are estimated with the compressive sensing approach based on angle grids, and the signal power together with the noise power are estimated. Thereafter, a modified steepest descent (SD) method is derived to recover the waveform of the desired signal and interferences utilizing the estimated power and directions. The recovered waveform of the desired signal is the output of the proposed method. The situation in which the signals are not on the predefined angle grids is also considered. The DOAs estimated via the predefined angle grids are corrected based on the maximum likelihood (ML) angle estimation. Compared to the existing beamforming methods on co-prime array, the proposed method can obtain the waveform of the desired signal. Simulation results demonstrate that the proposed method can achieve good performance in signal waveform recovery and output signal to noise ratio. © 2017 Beijing Institute of Aerospace Information.

Arrival time measurements of first arrival phases P and PKIKP using the method of fixed scale wavelet transformation ratio

The arrival times of first teleseismic phases are difficult to be measured precisely because of slowly and gradually changed onsets and weak amplitudes. The arrival times measured manually are usually behind the real ones. In this paper, using the ratio method of fixed scale wavelet transformations improved by us, the arrival times for the first arrival phases (such as P and PKIKP) at the teleseismic and far-teleseismic distances were measured. The results are reasonable and reliable based on the analysis and discussion of the reliabilities and errors.

Implementation of a Novel Algorithm on Acoustic Doppler Current Profiler Signal Processing System

Acoustic Doppler current profiler （ADCP） uses acoustic energy directed along narrow beams for current measurement. In conventional method, the quantity of sampling affects the precision of fast Fourier transform （FFT） algorithm, and the algorithm needs a large amount of data to process. A novel frequency estimator.enhanced least mean square （ELMS） algorithm for a single complex sinusoid in complex white Gaussian noise, is proposed in ADCP system. As sampling frequency equals 120 krad/s and the sampling number equals 240. the minimum resolving is 0. 5 krad/s. All variances keep 11.11%. ELMS algorithm needs less data than FFT. And the robust algorithm can estimate the spectrum true value to 99.9% when the signal to noise ratio （SNR） is equal to 0 dB. Experiments prove that the estimation values will diverge much from the ideal when SNR is less than -6 dB.

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.

3D Laser Imaging Reconstruction of Scenes Using New Photometric Gaussian Beam Range Equation

In this article the problem of three-dimensional （3-D） reconstruction of scenes from terrestrial laser rangefinder data is processed, we present the simulations results of radiometric range function of the laser range finder imaging system for better optimization of maximum range detection with a given SNR （Signal-to-noise ratio）. The study proposes a new reformulation of the radiometric Gaussian beam range equation on the basis of the photodetector active area. The adjustment of the optical and geometrical characteristics of the laser range finder so defined can be used to minimize the signal span to avoid the saturation of the detector cell and improve the ranging measurements （accuracy and range） for a 3D imaging application.

Stochastic resonance for signal-modulated pump noise in a single-mode laser

By adopting the gain-noise model of the single-mode laser in which with bias and periodical signals serve as inputs. combining with the effect of coloured pump） noise, we use the linear approximation method to calculate the power spectrum and signal-to-noise ratio （SNR） of the laser intensity under the condition of pump noise and quantum noise cross-related in the form of δ function. It is found that with the change of pump noise correlation time. both SNR and the output power will occur stochastic resonance （SR）. If the bias signal α is very small, changing the intensities of pump noise and quantum noise respectively does not lead to the appearance of SR in the SNR： while α increases to a certain number, SR appears.

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.