Analysis of the Influence of Sound Source Position and Electrode Placement on the Stimulation Pattern of the Cochlear Implant under Noise Conditions: Optimization of Auditory Perceptual Effects

Background: Cochlear implants (CI) are widely used to restore hearing in people with severe to profound hearing loss. However, optimizing CI performance, especially in difficult listening environments with background noise, remains a major challenge. Understanding the influence of factors such as sound source position and electrode placement on CI stimulation patterns is critical to improving auditory perception. Methods: In this study, an analysis was conducted to investigate the influence of sound source position and electrode placement on CI stimulation patterns under noisy conditions. For this purpose, a special measurement setup with a CI speech processor-microphone test box was used to simulate realistic listening scenarios and measure CI performance. Results: The results show that the effectiveness of CI noise reduction systems is influenced by factors such as the position of the sound source and electrode placement. In particular, the beamforming ultra zoom mode showed significantly better noise reduction than the omnidirectional mode, especially under real listening conditions. Furthermore, differences in electrode responses indicate individual variability in the CI user experience, highlighting the importance of personalized fitting algorithms. Conclusions: The results demonstrate the importance of considering environmental factors and individual differences when optimizing CI performance. Future research efforts should focus on the development of personalized fitting algorithms and the exploration of innovative strategies, such as the integration of artificial intelligence, to improve CI functionality in different listening environments. This study contributes to our understanding of CI stimulation patterns and lays the foundation for improving auditory perception in CI users.

Noise Reduction of an Axial Piston Pump by Valve Plate Optimization

Current researches mainly focus on the investigations of the valve plate utilizing pressure relief grooves. However,air?release and cavitation can occur near the grooves. The valve plate utilizing damping holes show excellent perfor?mance in avoiding air?release and cavitation. This study aims to reduce the noise emitted from an axial piston pump using a novel valve plate utilizing damping holes. A dynamic pump model is developed,in which the fluid properties are carefully modeled to capture the phenomena of air release and cavitation. The causes of di erent noise sources are investigated using the model. A comprehensive parametric analysis is conducted to enhance the understanding of the e ects of the valve plate parameters on the noise sources. A multi?objective genetic algorithm optimization method is proposed to optimize the parameters of valve plate. The amplitudes of the swash plate moment and flow rates in the inlet and outlet ports are defined as the objective functions. The pressure overshoot and undershoot in the piston chamber are limited by properly constraining the highest and lowest pressure values. A comparison of the various noise sources between the original and optimized designs over a wide range of pressure levels shows that the noise sources are reduced at high pressures. The results of the sound pressure level measurements show that the optimized valve plate reduces the noise level by 1.6 d B(A) at the rated working condition. The proposed method is e ective in reducing the noise of axial piston pumps and contributes to the development of quieter axial piston machines.

A local f-x Cadzow method for noise reduction of seismic data obtained in complex formations

A noise-reduction method with sliding called the local f-x Cadzow noise-reduction method, windows in the frequency-space （f-x） domain, is presented in this paper. This method is based on the assumption that the signal in each window is linearly predictable in the spatial direction while the random noise is not. For each Toeplitz matrix constructed by constant frequency slice, a singular value decomposition （SVD） is applied to separate signal from noise. To avoid edge artifacts caused by zero percent overlap between windows and to remove more noise, an appropriate overlap is adopted. Besides flat and dipping events, this method can enhance curved and conflicting events. However, it is not suitable for seismic data that contains big spikes or null traces. It is also compared with the SVD, f-x deconvolution, and Cadzow method without windows. The comparison results show that the local Cadzow method performs well in removing random noise and preserving signal. In addition, a real data example proves that it is a potential noise-reduction technique for seismic data obtained in areas of complex formations.

NOISE REDUCTION SCHEDULING METHOD IN A SHOP FLOOR AND ITS CASE STUDY

Noise reduction in a shop floor is one of the important parts of greenmanufacturing. In a shop floor machine tools are the main noise sources in a shop floor. A newapproach is discovered by investigation that the noise can be obviously reduced in a shop floor byoptimizing the scheduling between work pieces and machine tools. Based on the discovery, a newmethod of noise reduction is proposed. A noise reduction scheduling model in a shop floor isestablished, and the application of the model is also discussed. A case is studied, which shows thatthe method and model are practical.

Use of a plane jet for flow-induced noise reduction of tandem rods

Unsteady wake from upstream components of landing gear impinging on downstream components could be a strong noise source.The use of a plane jet is proposed to reduce this flow-induced noise.Tandem rods with different gap widths were utilized as the test body.Both acoustic and aerodynamic tests were conducted in order to validate this technique.Acoustic test results proved that overall noise emission from tandem rods could be lowered and tonal noise could be removed with use of the plane jet.However,when the plane jet was turned on,in some frequency range it could be the subsequent main contributor instead of tandem rods to total noise emission whilst in some frequency range rods could still be the main contributor.Moreover,aerodynamic tests fundamentally studied explanations for the noise reduction.Specifically,not only impinging speed to rods but speed and turbulence level to the top edge of the rear rod could be diminished by the upstream plane jet.Consequently,the vortex shedding induced by the rear rod was reduced,which was confirmed by the speed,Reynolds stress as well as the velocity fluctuation spectral measured in its wake.This study confirmed the potential use of a plane jet towards landing gear noise reduction.

A novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise,minimum mean square variance criterion and least mean square adaptive filter

Underwater acoustic signal processing is one of the research hotspots in underwater acoustics.Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing.Owing to the complexity of marine environment and the particularity of underwater acoustic channel,noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing.In order to solve the dilemma,we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN),minimum mean square variance criterion(MMSVC) and least mean square adaptive filter(LMSAF).This noise reduction technique,named CEEMDAN-MMSVC-LMSAF,has three main advantages:(i) as an improved algorithm of empirical mode decomposition(EMD) and ensemble EMD(EEMD),CEEMDAN can better suppress mode mixing,and can avoid selecting the number of decomposition in variational mode decomposition(VMD);(ii) MMSVC can identify noisy intrinsic mode function(IMF),and can avoid selecting thresholds of different permutation entropies;(iii) for noise reduction of noisy IMFs,LMSAF overcomes the selection of deco mposition number and basis function for wavelet noise reduction.Firstly,CEEMDAN decomposes the original signal into IMFs,which can be divided into noisy IMFs and real IMFs.Then,MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs.Finally,both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained.Compared with other noise reduction techniques,the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals,which has the better noise reduction effect and has practical application value.CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection,feature extraction,classification and recognition of underwater acoustic signals.

Joint Noise Reduction and lp-Norm Minimization for Enhancing Time Delay Estimation in Colored Noise

Time delay estimation (TDE) is an important issue in signal processing. Conventional TDE algorithms are usually efficient under white noise environments. In this paper, a joint noise reduction and -norm minimization method is presented to enhance TDE in colored noise. An improved subspace method for colored noise reduction is first performed. Then the time delay is estimated by using an -norm minimization method. Because the clean speech signal form the noisy signal is well extracted by noise reduction and the -norm minimization method is robust, the TDE accuracy can be enhanced. Experiment results confirm that the proposed joint estimation method obtains more accurate TDE than several conventional algorithms in colored noise, especially in the case of low signal-to-noise ratio.

Hybrid device for acoustic noise reduction and energy harvesting based on a silicon micro-perforated panel structure

A kind of hybrid device for acoustic noise reduction and vibration energy harvesting based on the silicon micro- perforated panel （MPP） resonant structure is investigated in the article. The critical parts of the device include MPP and energy harvesting membranes. They are all fabricated by means of silicon micro-electro-mechanical systems （MEMS） tech- nology. The silicon MPP has dense and accurate micro-holes. This noise reduction structure has the advantages of wide band and higher absorption coefficients. The vibration energy harvesting part is formed by square piezoelectric membranes arranged in rows. ZnO material is used as it has a good compatibility with the fabrication process. The MPP, piezo- electric membranes, and metal bracket are assembled into a hybrid device with multifunctions. The device exhibits good performances of acoustic noise absorption and acoustic-electric conversion. Its maximum open circuit voltage achieves 69.41 mV.

Hybrid In-Vehicle Background Noise Reduction for Robust Speech Recognition:The Possibilities of Next Generation 5G Data Networks

This pilot study focuses on employment of hybrid LMS-ICA system for in-vehicle background noise reduction.Modern vehicles are nowadays increasingly supporting voice commands,which are one of the pillars of autonomous and SMART vehicles.Robust speaker recognition for context-aware in-vehicle applications is limited to a certain extent by in-vehicle back-ground noise.This article presents the new concept of a hybrid system which is implemented as a virtual instrument.The highly modular concept of the virtual car used in combination with real recordings of various driving scenarios enables effective testing of the investigated methods of in-vehicle background noise reduction.The study also presents a unique concept of an adaptive system using intelligent clusters of distributed next generation 5G data networks,which allows the exchange of interference information and/or optimal hybrid algorithm settings between individual vehicles.On average,the unfiltered voice commands were successfully recognized in 29.34%of all scenarios,while the LMS reached up to 71.81%,and LMS-ICA hybrid improved the performance further to 73.03%.

Fault Diagnosis of Wind Turbine Generator with Stacked Noise Reduction Autoencoder Based on Group Normalization

In order to improve the condition monitoring and fault diagnosis of wind turbines,a stacked noise reduction autoencoding network based on group normalization is proposed in this paper.The network is based on SCADA data of wind turbine operation,firstly,the group normalization(GN)algorithm is added to solve the problems of stack noise reduction autoencoding network training and slow convergence speed,and the RMSProp algorithm is used to update the weight and the bias of the autoenccoder,which further optimizes the problem that the loss function swings too much during the update process.Finally,in the last layer of the network,the softmax activation function is used to classify the results,and the output of the network is transformed into a probability distribution.The selected wind turbine SCADA data was substituted into the pre-improved and improved stacked denoising autoencoding(SDA)networks for comparative training and verification.The results show that the stacked denoising autoencoding network based on group normalization is more accurate and effective for wind turbine condition monitoring and fault diagnosis,and also provides a reference for wind turbine fault identification.

Artificial neural network-based determination of denoised optical properties in double integrating spheres measurement

Accurate determination of the optical properties of biological tissues enables quantitative understanding of light propagation in these tissues for optical diagnosis and treatment applications.The absorption(μa)and scattering(μs)coe±cients of biological tissues are inversely analyzed from their diffuse re°ectance(R)and total transmittance(T),which are measured using a double integrating spheres(DIS)system.The inversion algorithms,for example,inverse adding doubling method and inverse Monte Carlo method,are sensitive to noise signals during the DIS measurements,resulting in reduced accuracy during determination.In this study,we propose an arti ficial neural network(ANN)to estimateμa andμs at a target wavelength from the R and T spectra measured via the DIS to reduce noise in the optical properties.Approximate models of the optical properties and Monte Carlo calculations that simulated the DIS measurements were used to generate spectral datasets comprisingμa,μs,R and T.Measurement noise signals were added to R and T,and the ANN model was then trained using the noise-added datasets.Numerical results showed that the trained ANN model reduced the effects of noise inμa andμs estimation.Experimental veri fication indicated noise-reduced estimation from the R and T values measured by the DIS with a small number of scans on average,resulting in measurement time reduction.The results demonstrated the noise robustness of the proposed ANN-based method for optical properties determination and will contribute to shorter DIS measurement times,thus reducing changes in the optical properties due to desiccation of the samples.

The noise spectral characteristics and noise reduction schemes of screw air-source heat pump:A case study

The screw air-source heat pump can cause incessant high noise levels during operation,which might hinder adoption of this energy-efficient heat pump.First,acoustic measurements and comparison testing were performed in this research.The measurements revealed that the compressor is the main noise source of the heat pump,and it shows a multipeak frequency distribution and a wide frequency spectrum under different work conditions,with multiple peaks at 63,250,and 1000 Hz.Then,a compressor sound insulation cover with broadband absorption was proposed,and it was experimentally proven that the insulation cover can reduce the maximum sound pressure level of one unit from 89.8 dBA to 79.1 dBA.Third,we proposed several noise reduction strategies and compared their noise reduction effects using computer simulation.The results showed that the noise problem can be effectively improved through the rational design of the sound barrier and the layout and opening options of heat pump.The distance between the sound barrier and heat pump and the sound attenuation due to diffraction ALa exhibit a U-shaped relation.For buildings of different heights,the optimal heights of noise barrier are proposed.The 5.5-meter is the optimal height of the sound barrier for single-story buildings.The conclusions can be applied to other building projects for heat pump noise reduction.

Optimal Design and Experimental Verification of Low Radiation Noise of Gearbox

Reducing the radiated noise of a gearbox is a difficult problem in aviation,navigation,machinery,and other fields.Structural improvement is the main means of noise reduction for a gearbox,and it is realized primarily through contribution analysis and structure optimization.However,these approaches have certain limitations.In this study,a low-noise design method for a gearbox that combines the two approaches is proposed,and experimental verification is performed.First,a finite element/boundary element model is established using a single-stage herringbone gearbox.Considering the vibration excitation of the gear system,the radiation noise of a single-stage gearbox is predicted based on the modal acoustic transfer vector(MATV)method.Subsequently,the maximum field point of the radiated noise is determined,and the acoustic transfer vector(ATV)analysis and modal acoustic contribution(MAC)analysis are conducted to determine the region that contributes significantly to the radiated noise of the field point.The optimization region is selected through the panel acoustic contribution(PAC)analysis.Next,to reduce the normal speed in the optimization region,topology optimization is performed.According to the topology optimization results,four different noise reduction structures are added to the gearbox,and the low-noise optimization models are established respectively.Finally,by measuring the radiated noise of the gearbox before and after optimization under a given working condition,the validity of the radiated noise prediction method and the low-noise optimization design method are verified by comparing the simulation and experimental data.A comparison of the four optimization models proves that the noise reduction effect can be achieved only by adding a noise reduction structure to the center of the density nephogram.

PREDICTION TECHNIQUES OF CHAOTIC TIME SERIES AND ITS APPLICATIONS AT LOW NOISE LEVEL

The paper not only studies the noise reduction methods of chaotic time series with noise and its reconstruction techniques, but also discusses prediction techniques of chaotic time series and its applications based on chaotic data noise reduction. In the paper, we first decompose the phase space of chaotic time series to range space and null noise space. Secondly we restructure original chaotic time series in range space. Lastly on the basis of the above, we establish order of the nonlinear model and make use of the nonlinear model to predict some research. The result indicates that the nonlinear model has very strong ability of approximation function, and Chaos predict method has certain tutorial significance to the practical problems.

Simultaneous Speckle Reduction and SAR Image Compression Using Multiwavelet Transform

Synthetic aperture radar （SAR） images are corrupted by multiplicative speckle noise which limits the performance of the classical coder/decoder algorithm in spatial domain. The relatively new transform of multiwavelets can possess desirable features simultaneously, such as orthogonality and symmetry, while scalar wavelets cannot. In this paper we propose a compression scheme combining with speckle noise reduction within the multiwavelet framework. Compared with classical set partitioning in hierarchical trees （SPIHT） algorithm, our method achieves favorable peak signal to noise ratio （PSNR） and superior speckle noise reduction performances.

A practical and effective method for reducing differential reflectance spectroscopy noise

Differential reflectance spectroscopy(DRS)is a powerful tool to study processes during thin-film growth,especially that of transition metal dichalcogenides and organic thin films.To satisfy the requirements for in situ and real-time monitoring of film growth,including spectral resolution and sensitivity at the level of monolayers and even sub-monolayers,the most challenging technical task in DRS is to reduce noise to an extremely low level so that the best possible signal-to-noise ratio can be achieved.In this paper,we present a simplified and cost-effective DRS apparatus,with which we show that the measurement noise is mainly composed of thermal drift noise and explore the temperature-dependence of the DRS signal.Based on the results obtained,we propose an easily realized and effective scheme aiming to reduce the noise.Experimental results demonstrate that this scheme is effective in stabilizing reliable signals for a long period of several hours.Significant noise reduction is achieved,with the typical average noise of the DRS system being decreased to 0.05%over several hours.The improved DRS system is applied to study the growth of an organic semiconductor layer for an organic field-effect transistor device.The results indicate that the apparatus proposed in this paper has potential applications in fabrication of devices on the nanoscale and even the sub-nanoscale.

Hydrodynamic characteristics and noise reduction mechanism of a wave leading hydrofoil placed in the wake of a cylinder

We have investigated the hydrodynamic and acoustic performance of a hydrofoil with a wave leading edge that is being ingested in a cylindrical wake,to explore the interaction and noise reduction mechanism with the use of near flow field and far field noise decoupled prediction methods of large eddy simulation(LES)and Ffowcs Williams-Hawkings(FW-H).Our results indicate that the wave leading edge has minimal effect on the hydrodynamic performance,however,it has demonstrated the ability to significantly improve the acoustic performance.Through the comparison of sound pressure level(SPL)and acoustic directivity,we have observed that the wave leading edge can significantly reduce the broadband noise in the far field.This is due to its ability to break the large-scale structure of the incoming flow,which weakens the direct impact and therefore reduces the tone noise.Additionally,the interaction between the broken vortex and the boundary layer around the hydrofoil surface is weakened,leading to a reduction in surface pressure pulsation and broadband noise intensity.The wave structure primarily affects the flow structure near the leading edge,resulting in a reduction in flow disturbance and sound source intensity,and an improvement in the acoustic feedback loop between the foil and the fore-cylinder.

Vibration and Sound Radiation of Cylindrical Shell Covered with a Skin Made of Micro Floating Raft Arrays Excited by Turbulence

To reduce the vibration and sound radiation of underwater cylindrical shells,a skin composed of micro floating raft arrays and a compliant wall is proposed in this paper.A vibroacoustic coupling model of a finite cylindrical shell covered with this skin for the case of turbulence excitation is established based on the shell theories of Donnell.The model is solved with the modal superposition method to investigate the effects of the structural parameters of micro floating raft elements on the performance of reducing vibration and sound radiation of the cylindrical shell of this skin.The results indicate that increasing the stiffness ratio,damping ratio,mass ratio,or decreasing the interval betweenmicro floating raft elements can improve the vibration and sound radiation reduction performance of this skin over the frequency range 0∼2000 Hz.Moreover,the mean quadratic velocity level and sound radiation power level of the finite cylindrical shell with this skin can be reduced by 12.00 dB and 9.65 dB respectively compared to the finite cylindrical shell with homogeneous viscoelastic coating in the frequency range from0∼2000Hz,implying a favorable performance of this skin for reducing the vibration and sound radiation of cylindrical shells.

An Optimized Implementation of a Novel Nonlinear Filter for Color Image Restoration

Image processing is becoming more popular because images are being used increasingly in medical diagnosis,biometric monitoring,and character recognition.But these images are frequently contaminated with noise,which can corrupt subsequent image processing stages.Therefore,in this paper,we propose a novel nonlinear filter for removing“salt and pepper”impulsive noise from a complex color image.The new filter is called the Modified Vector Directional Filter(MVDF).The suggested method is based on the traditional Vector Directional Filter(VDF).However,before the candidate pixel is processed by the VDF,theMVDF employs a threshold and the neighboring pixels of the candidate pixel in a 3×3 filter window to determine whether it is noise-corrupted or noise-free.Several reference color images corrupted by impulsive noise with intensities ranging from 3%to 20%are used to assess theMVDF’s effectiveness.The results of the experiments show that theMVDF is better than the VDF and the Generalized VDF(GVDF)in terms of the PSNR(Peak Signal-to-Noise Ratio),NCD(Normalized Color Difference),and execution time for the denoised image.In fact,the PSNR is increased by 6.554%and 12.624%,the NCD is decreased by 20.273%and 44.147%,and the execution time is reduced by approximately a factor of 3 for the MVDF relative to the VDF and GVDF,respectively.These results prove the efficiency of the proposed filter.Furthermore,a hardware design is proposed for the MVDF using the High-Level Synthesis(HLS)flow in order to increase its performance.This design,which is implemented on the Xilinx ZynqXCZU9EG Field-ProgrammableGate Array(FPGA),allows the restoration of a 256×256-pixel image in 2 milliseconds(ms)only.

Determination of the Sound Absorption Capacity of Hydraulic Concrete Mixtures Added with Waste Tire Rubber

There are different types of pollutants that are harmful to the environment, including smog, chemicals that are dumped into rivers, scrap tires, etc. The latter have the particularity that it is not possible to recycle them to manufacture new tires. In the present work, hydraulic concrete plates added with waste tire rubber were manufactured to modify their sound absorption capacity. It was found that the rubber additions produce changes in the density of the material and in the sound absorption capacity. When the material is exposed to high-frequency sounds that correspond to high-pitched sounds, its absorption capacity increases. On the contrary, when the test frequency is low, that is, bass sounds, the sound absorption capacity decreases. The results obtained in this work suggest that the proposed mixtures are suitable for the possible manufacture of acoustic insulating shields.