Seismic Noise Suppression for Ground-Based Investigation of an Inertial Sensor by Suspending the Electrode Cage

Performance test of a high precise accelerometer or an inertial sensor on the ground is inevitably limited by the seismic noise. A torsion pendulum has been used to investigate the performances of an electrostatic accelerometer, where the test mass is suspended by a fiber to compensate for its weight, and this scheme demonstrates an advantage, compared with the high-voltage levitation scheme, in which the effect of the seismic noise can be suppressed for a few orders of magnitude in low frequencies. In this work, the capacitive electrode cage is proposed to be suspended by another pendulum, and theoretical analysis shows that the effects of the seismic noise can be further suppressed for more than one order by suspending the electrode cage.

Elastic-Wave Reverse Time Migration Random Boundary-Noise Suppression Based on CycleGAN

In elastic-wave reverse-time migration(ERTM),the reverse-time reconstruction of source wavefield takes advantage of the computing power of GPU,avoids its disadvantages in disk-access efficiency and reading and writing of temporary files,and realizes the synchronous extrapolation of source and receiver wavefields.Among the existing source wavefield reverse-time reconstruction algorithms,the random boundary algorithm has been widely used in three-dimensional(3D)ERTM because it requires the least storage of temporary files and low-frequency disk access during reverse-time migration.However,the existing random boundary algorithm cannot completely destroy the coherence of the artificial boundary reflected wavefield.This random boundary reflected wavefield with a strong coherence would be enhanced in the cross-correlation image processing of reverse-time migration,resulting in noise and fictitious image in the migration results,which will reduce the signal-to-noise ratio and resolution of the migration section near the boundary.To overcome the above issues,we present an ERTM random boundary-noise suppression method based on generative adversarial networks.First,we use the Resnet network to construct the generator of CycleGAN,and the discriminator is constructed by using the PatchGAN network.Then,we use the gradient descent methods to train the network.We fix some parameters,update the other parameters,and iterate,alternate,and continuously optimize the generator and discriminator to achieve the Nash equilibrium state and obtain the best network structure.Finally,we apply this network to the process of reverse-time migration.The snapshot of noisy wavefield is regarded as a 2D matrix data picture,which is used for training,testing,noise suppression,and imaging.This method can identify the reflected signal in the wavefield,suppress the noise generated by the random boundary,and achieve denoising.Numerical examples show that the proposed method can significantly improve the imaging quality of ERTM.

Shot Noise Suppression in a Quantum Point Contact with Short Channel Length

An experimental study on the current shot noise of a quantum point contact with short channel length is reported. The experimentally measured maximum energy level spacing between the ground and the first excited state of the device reached up to 7.5meV, probably due to the hard wall confinement by using shallow electron gas and sharp point contact geometry. The two-dimensionM non-equilibrium shot noise contour map shows noise suppression characteristics in a wide range of bias voltage. Fano factor analysis indicates spin-polarized transport through a short quantum point contact.

Design of Background Noise Suppression Circuit for Mobile Phones

With the purpose of reducing the influence of background noise on the call quality of mobile phones, background noise suppression circuit is designed based on the principle of self-adaptive noise cancellation. Because this method is not involved in the nature of the noise itself, it can be used both for stationary noise cancellation and quasi-stationary noise cancellation. The working principle and circuit design of the system are introduced in detail. Simulated experiment was conducted in the lab, and its experimental results were analyzed. The experimental results show that the circuit works well with low cost, and has a broad prospect of application and popularization.

A Noise Suppression Method for Speech Signal by Jointly Using Bayesian Estimation and Fuzzy Theory

Speech recognition systems have been applied to inspection and maintenance operations in industrial factories to recording and reporting routines at construction sites, etc. where hand-writing is difficult. In these actual circumstances, some countermeasure methods for surrounding noise are indispensable. In this study, a new method to remove the noise for actual speech signal was proposed by using Bayesian estimation with the aid of bone-conducted speech and fuzzy theory. More specifically, by introducing Bayes’ theorem based on the observation of air-conducted speech contaminated by surrounding background noise, a new type of algorithm for noise removal was theoretically derived. In the proposed noise suppression method, bone-conducted speech signal with the reduced high-frequency components was regarded as fuzzy observation data, and a stochastic model for the bone-conducted speech was derived by applying the probability measure of fuzzy events. The proposed method was applied to speech signals measured in real environment with low SNR, and better results were obtained than an algorithm based on observation of only air-conducted speech.

Precision measurement and suppression of low-frequency noise in a current source with double-resonance alignment magnetometers

Low-noise high-stability current sources have essential applications such as neutron electric dipole moment measurement and high-stability magnetometers. Previous studies mainly focused on frequency noise above 0.1 Hz while less on the low-frequency noise/drift. We use double resonance alignment magnetometers(DRAMs) to measure and suppress the low-frequency noise of a homemade current source(CS) board. The CS board noise level is suppressed by about 10 times in the range of 0.001-0.1 Hz and is reduced to 100 n A/√Hz at 0.001 Hz. The relative stability of CS board can reach2.2 × 10^(-8). In addition, the DRAM shows a better resolution and accuracy than a commercial 7.5-digit multimeter when measuring our homemade CS board. Further, by combining the DRAM with a double resonance orientation magnetometer,we may realize a low-noise CS in the 0.001-1000 Hz range.

Noise suppression for the detection laser of a nuclear magnetic resonance gyroscope based on a liquid crystal variable retarder

Nuclear magnetic resonance gyroscopes （NMRGs） are a kind of rotation-speed sensor that senses the angular velocity by measuring a frequency shift in the Larmor pre- cession of the nuclear spin in a constant magnetic field.

Towed line array sonar platform noise suppression based on spatial matrix filtering technology

The spatial matrix filter was designed and used for solving the problem to detect a weak target who was influenced by the strong nearby platform noise interference of the towed line array sonar. The MFP technology and the DOA estimation technology were combined together by using the sound propagation characteristics of both target and interference. The spatial matrix filter with platform noise zero response constraint was designed by the near-field platform noise normal modes copy vectors and the far-field plane wave bearing vectors together. The optimal solution of the optimization problem for designing the spatial matrix filter was deduced directly, and it was simplified by the generalized singular value decomposition. The total response error to the plane wave bearing vectors and the total response to the platform noise copy vectors were given. The phenomena that strong interferences existed in the bearing course and blind areas existed after filtering were analyzed by the correlation between the plat- form noise copy vectors and the plane wave bearing vectors. It could be found from simulations that it has less blind area and higher detection ability by using the spatial matrix filtering technology.

A Δ ∑ fractional-N frequency synthesizer for FM tuner using low noise filter and quantization noise suppression technique

A △∑ fractional-N frequency synthesizer fabricated in a 130 nm CMOS technology is presented for the application of an FM tuner. A low noise filter, occupying a small die area and decreasing the output noise, is integrated on a chip. A quantization noise suppression technique, using a reduced step size of the frequency divider, is also adopted. The proposed synthesizer needs no off-chip components and occupies an area of 0.7 mm2. The in-band phase noise （from 10 to 100 kHz） below -108 dBc/Hz and out-of-band phase noise of -122.9 dBc/Hz （at 1 MHz offset） are measured with a loop bandwidth of 200 kHz. The quantization noise suppression technique reduces the in-band and out-of band phase noise by 15 dB and 7 dB respectively. The integrated RMS phase error is no more than 0.48°. The proposed synthesizer consumes a total power of 7.4 mW and the frequency resolution is less than 1 Hz.

On-Line Suppression of Periodic Noises in Evoked Potentials

Under clinical conditions,the major components of noises in human evoked potentialsare periodic impulses,such as power interferences, system oscillations. Reducing their effects by analogfilter is inevitably associated with the distortions of the signal of interest.In this paper,a new approachto suppress periodic noises is presented using time-domain operators which are applied on the individualdigitized responses before averaging.A new algorithm for real time processing is developed.The effectiveness of the algorithm in dealing with simulated as well as actual evoked responses is demonstrated.The results show that this algorithm has good performance in periodic noise suppression and has zerophase shift, thus it is very suitable to be implemented on biomedical instrumentations used inclinical setups.

High Permeability in Broadband of Co-sputtered [Fe-Fe_(20)Ni_(80)/Cr]_(n) Multilayer Films

To achieve high microwave permeability in wide-band for the micron-thick magnetic films,[Fe-Fe_(20)Ni_(80)/Cr]_(n) multilayer structure was proposed by co-sputtering Fe and FeNi to form the magnetic layers and Cr to form the interlayers.The multilayer structure contributes to the high permeability by reducing the coercivity and diminishing out-of-plane magnetization.The maximum imaginary permeability of[Fe-Fe_(20)Ni_(80)/Cr]_(n) multilayer film reaches a large value of 800 at 0.52 GHz even though its overall thickness exceeds 1μm.Besides,the magnetic resonance frequency of the multilayer film can be modulated from 0.52 to 1.35 GHz by adjusting the sputtering power of Fe from 0 to 86 W,and its bandwidth for μ’’>200(Δf) is as large as 2.0 GHz.The desirable broad Δf of magnetic permeability,which can be well fitted by the Landau-Lifshitz-Gilbert equations,is due to dual magnetic resonances originated from double magnetic phases of Fe and FeNi that are of different saturation magnetization.The micron-thick multilayer films with high permeability in extended waveband are promising candidate for electromagnetic noise suppression application.

Simultaneously Suppressing Low-Frequency and Relaxation Oscillation Intensity Noise in a DBR Single-Frequency Phosphate Fiber Laser

Effective multiple optoelectronic feedback circuits for simultaneously suppressing low-frequency and relaxation oscillation intensity noise in a single-frequency phosphate fiber laser are demonstrated. The forward transfer function, which relates the laser output intensity to the pump modulations, is measured and analyzed. A custom two-path feedback system operating at different frequency bands is designed to adjust the pump current directly. The relative intensity noise is decreased by 20dB from 0.2 to 5kHz and over lOdB from 5 to lOkHz. The relaxation oscillation peak is suppressed by 22dB. In addition, a long term （24h） laser instability of less than 0.05% is achieved.

Real-Time Speech Enhancement Based on Convolutional Recurrent Neural Network

Speech enhancement is the task of taking a noisy speech input and pro-ducing an enhanced speech output.In recent years,the need for speech enhance-ment has been increased due to challenges that occurred in various applications such as hearing aids,Automatic Speech Recognition(ASR),and mobile speech communication systems.Most of the Speech Enhancement research work has been carried out for English,Chinese,and other European languages.Only a few research works involve speech enhancement in Indian regional Languages.In this paper,we propose a two-fold architecture to perform speech enhancement for Tamil speech signal based on convolutional recurrent neural network(CRN)that addresses the speech enhancement in a real-time single channel or track of sound created by the speaker.In thefirst stage mask based long short-term mem-ory(LSTM)is used for noise suppression along with loss function and in the sec-ond stage,Convolutional Encoder-Decoder(CED)is used for speech restoration.The proposed model is evaluated on various speaker and noisy environments like Babble noise,car noise,and white Gaussian noise.The proposed CRN model improves speech quality by 0.1 points when compared with the LSTM base model and also CRN requires fewer parameters for training.The performance of the pro-posed model is outstanding even in low Signal to Noise Ratio(SNR).

Suppression of backscattering induced noise by the sideband locking technique in a resonant fiber optic gyroscope

Polarization fluctuation induced noise and backscattering-induced noise are the dominant noises in resonant fiber optic gyroscopes. This Letter proposes a new method to suppress the carrier and backscattering induced noise by the sideband locking technique. Besides choosing an optimized modulation depth and different clockwise and counterclockwise modulation frequencies, the sideband is locked to the cavity resonance. With the proper modulation frequency, the carrier frequency component locates at a position far away from the resonant frequency, and then it is suppressed by the cavity itself, which can be taken as a bandpass filter. The amplitude of the carrier frequency can be suppressed by 20–25 d B additionally by the cavity and the total intensity suppression ratio can reach 115.74 d B. The backscattering induced noise can be eliminated for the adoption of different frequencies. The method can realize a stable and high suppression ratio without high requirements for parameter accuracy or device performance.

Abdominal Fat Distribution and the Clustering Risk Factor for Cardiovascular

Under clinical conditions,the major components of noises in human evoked potentialsare periodic impulses,such as power interferences, system oscillations. Reducing their effects by analogfilter is inevitably associated with the distortions of the signal of interest.In this paper,a new approachto suppress periodic noises is presented using time-domain operators which are applied on the individualdigitized responses before averaging.A new algorithm for real time processing is developed.The effectiveness of the algorithm in dealing with simulated as well as actual evoked responses is demonstrated.The results show that this algorithm has good performance in periodic noise suppression and has zerophase shift, thus it is very suitable to be implemented on biomedical instrumentations used inclinical setups.

Electromagnetic interference modeling and suppression techniques in variable-frequency drive systems

Electromagnetic interference （EMI） causes electromechanical damage to the motors and degrades the reliability of variable-frequency drive （VFD） systems. Unlike fundamental frequency components in motor drive systems, high-frequency EMI noise, coupled with the parasitic parameters of the trough system, are difficult to analyze and reduce. In this article, EMI modeling techniques for different function units in a VFD system, including induction motors, motor bearings, and rectifierinverters, are reviewed and evaluated in terms of applied frequency range, model parameterization, and model accuracy. The EMI models for the motors are categorized based on modeling techniques and model topologies. Motor bearing and shaft models are also reviewed, and techniques that are used to eliminate bearing current are evaluated. Modeling techniques for conventional rectifierinverter systems are also summarized. EMI noise suppres- sion techniques, including passive filter, Wheatstone bridge balance, active filter, and optimized modulation, are reviewed and compared based on the VFD system models.

Study of Time Delay Estimation for Multichannel Noise Suppresion System

Accurate time delay estimation is very important in multichannel noise suppression systems. This paper has proposed a new method to reduce the effect of noise on the estimation of time delay between different channels. Our new time delay algorithm will more considerably reduce the estimation error, compared with the conventional autocorrelation function method.

Overview of Planar Magnetics for High-frequency Resonant Converters

With the continuous development of power supplies toward miniaturization,light weights,and high levels of integration,research on high-frequency resonant conversion based on planar magnetics is becoming extensive.Combining the soft-switching characteristics of resonant converters with those of wide bandgap devices,the switching frequency can be increase to the MHz range,and the power density of the entire system can be improved considerably.However,higher switching frequencies impose new requirements for the structural design,loss distribution,and common mode(CM)noise suppression of passive magnetic components.Herein,a thorough survey of the-state-of-the-art of planar magnetics in high-frequency resonant converters is conducted.Printed circuit board winding-based planar magnetics,magnetic integration,and power-loss optimization strategies are summarized in detail.Suppression methods for CM noise in high-frequency planar magnetics are also clarified and discussed.An insight view into the future development of planar magnetics for high-frequency resonant converters is presented.

True Amplitude Extraction Technology and Its Application in Pre-Stack Seismic Data

Common-reflection-point （CRP） gather is a bridge that connects seismic data and petro- physical parameters. Pre-stack attributes extraction and pre-stack inversion, both of them are impor- tant means of reservoir prediction. Quality of CRP gather usually has great impact on the accuracy of seismic exploration. Therefore, pre-stack CRP gathers noise suppression technology becomes a major research direction. Based on the vector decomposition principle, here we propose a method to suppress noise. This method estimates optimal unit vectors by searching in various directions and then sup- presses noise through vector angle smoothing and restriction. Model tests indicate that the proposed method can separate effective signal from noise very well and suppress random noise effectively in single wavenumber case. Application of our method to real data shows that the method can recover effective signal with good amplitude preserved from pre-stack noisy seismic data even in the case of low signal to noise ratio （SNR）.

Skin Segmentation Based on Graph Cuts

Skin segmentation is widely used in many computer vision tasks to improve automated visualiza- tion. This paper presents a graph cuts algorithm to segment arbitrary skin regions from images. The detected face is used to determine the foreground skin seeds and the background non-skin seeds with the color probability distributions for the foreground represented by a single Gaussian model and for the background by a Gaussian mixture model. The probability distribution of the image is used for noise suppression to alle- viate the influence of the background regions having skin-like colors. Finally, the skin is segmented by graph cuts, with the regional parameter y optimally selected to adapt to different images. Tests of the algorithm on many real world photographs show that the scheme accurately segments skin regions and is robust against illumination variations, individual skin variations, and cluttered backgrounds.