Random noise suppression for seismic data using a non-local Bayes algorithm

For random noise suppression of seismic data, we present a non-local Bayes （NL- Bayes） filtering algorithm. The NL-Bayes algorithm uses the Gaussian model instead of the weighted average of all similar patches in the NL-means algorithm to reduce the fuzzy of structural details, thereby improving the denoising performance. In the denoising process of seismic data, the size and the number of patches in the Gaussian model are adaptively calculated according to the standard deviation of noise. The NL-Bayes algorithm requires two iterations to complete seismic data denoising, but the second iteration makes use of denoised seismic data from the first iteration to calculate the better mean and covariance of the patch Gaussian model for improving the similarity of patches and achieving the purpose of denoising. Tests with synthetic and real data sets demonstrate that the NL-Bayes algorithm can effectively improve the SNR and preserve the fidelity of seismic data.

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.

Novel Retinex algorithm by interpolation and adaptive noise suppression

In order to improve image quality, a novel Retinex algorithm for image enhancement was presented. Different from conventional algorithms, it was based on certain defined points containing the illumination information in the intensity image to estimate the illumination. After locating the points, the whole illumination image was computed by an interpolation technique. When attempting to recover the reflectance image, an adaptive method which can be considered as an optimization problem was employed to suppress noise in dark environments and keep details in other areas. For color images, it was taken in the band of each channel separately. Experimental results demonstrate that the proposed algorithm is superior to the traditional Retinex algorithms in image entropy.

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.

SMART STRUCTURES USING PIEZOELEMENTS FOR ACTIVE VIBRATION AND NOISE SUPPRESSION IN AVIATION AND AEROSPACE

Smart material and structure (SMS) is a challenging novel technique for the 21 century especially in fields of aviation and aerospace. Vibration and noise suppression smart structure is an important branch of SMS. There are several typical structures such as the cabin of an airplane, space station, the solar board of satellite and the rotor blade of a helicopter, of which the vibrations and radiation noises have bad influences on precise equipments and aiming systems. In order to suppress vibrations and noises of these structures, several algorithms are applied to the models which simulate the structures. Experiments are performed to suppress vibrations and noises by bonding sensors and actuators to the structures at the optimized locations and using computer based measurement and control systems. For the blade vibration control of a helicopter, a non contact method of signal transmission by magneto electric coupling is discussed. The experimental results demonstrate that the methods used for active control are effective.

Intensity Noise Suppression of an FP Laser by External Injection Locking

The optimal intensity noise suppression of a Fabry-Perot （FP） laser is experimentally acquired by relatively strong external optical injection locking technology. The maximum suppression is up to 9dB around the relaxation oscillation peak of the free running FP laser. We demonstrate how the injection light power and detuning frequency influence the intensity noise suppression effects. Additionally, the relationship between the optimal suppression range and the stable locking range is experimentally studied：both ranges enlarge as the injection light power increases, but the stable locking range permits larger detuning frequency at identical injection light power.

Performance Improvement of Raman Distributed Temperature System by Using Noise Suppression

In Raman distributed temperature system, the key factor for performance improvement is noise suppression, which seriously affects the sensing distance and temperature accuracy. Therefore, we propose and experimentally demonstrate dynamic noise difference algorithm and wavelet transform modulus maximum （WTMM） to de-noising Raman anti-Stokes signal. Experimental results show that the sensing distance can increase from 3 kin to 11.5 km and the temperature accuracy increases to 1.58 ℃ at the sensing distance of 10.4kin.

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.

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.

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.

Suppression of Speckle in SAR Images Using Wavelet-Based HMM

In order to suppress the speckle appearing in synthesis aperture radar (SAR) images, a novel speckle reduction method based on wavelet domain hidden Markov tree (HMT) was proposed. First, the image was logarithmic transformed to change the statistical property of the speckles. Then an HMT was constructed in the correspondent wavelet domain. Based on this model, the image signal was restored by maximum likelihood estimation and speckle noise was suppressed. Simulating SAR images had shown that the performance of the filter is satisfactory for both speckle smoothing and edges presentation, and for generating visually natural images as well.

Noise degradation system using Wiener filter and CORDIC based FFT/IFFT processor

On augmentation of past work, an effective Wiener filter and its application for noise suppression combined with a formed CORDIC based FFT/IFFT processor with improved speed were executed. The pipelined methodology was embraced for expanding the execution of the system. The proposed Wiener filter was planned in such an approach to evacuate the iteration issues in ordinary Wiener filter. The division process was supplanted by a productive inverse and multiplication process in the proposed design. An enhanced design for matrix inverse with reduced computation complexity was executed. The wide-ranging framework processing was focused around IEEE-754 standard single precision floating point numbers. The Wiener filter and the entire system design was integrated and actualized on VIRTEX 5 FPGA stage and re-enacted to approve the results in Xilinx ISE 13.4. The results show that a productive decrease in power and area is developed by adjusting the proposed technique for speech signal noise degradation with latency of n/2 clock cycles and substantial throughput result per every 12 clock cycles for n-bit precision. The execution of proposed design is exposed to be 31.35% more effective than that of prevailing strategies.

Acoustic Resonance in Exhaust Gas Economizer Tube Bundles Prediction and Suppression of Resonance

The tendency for air column resonance generation in structures with a constant volume behind a tube array like that of an exhaust gas economizer has been reported, but many points remain unclear with respect to the mechanism and conditions that generate acoustical resonance. When acoustical resonance is generated, in reality, prevention and suppression measures are implemented by inserting a baffle plate into the ducts through a process of trial and error. The purpose of this study is to clarify the mechanism of generation of acoustical resonance, and to establish an appropriate measure to prevent such resonance. Noise generated in an exhaust gas economizer was correlated with the flow inside the tube array and experimentally analyzed, and the mechanism for resonance generation was considered. In addition, the effectiveness of a baffle plate positioned in order to prevent resonance was investigated. We have successfully employed a single baffle plate to suppress resonance.