Active Cancelation of Acoustic Noise in Waveguides by Standard Control Task Decision Usage

Cybernetic decision variants were analyzed in order to use for physical task of active noise cancelation. 10 dB mean active noise cancellation is demonstrated in two decades frequency band by usage of cybernetic decision for acoustical duct physical scale model. The used decision was found on minimization of acoustical field power transfer function from the beginning of waveguide to their end.

Advanced surface coil layout with intrinsic noise cancellation properties for surface-NMR applications

A recent study demonstrated that in small-scale prepolarized surface nuclear magnetic resonance(SNMR-PP)measurements with a footprint of a few square meters,customized PP switch-off ramps can serve as an efficient excitation mechanism,eliminating the requirement for a conventional oscillating excitation pulse.This approach enables the detection of short relaxation signals from the unsaturated soil zone and can,therefore,be used to directly provide soil moisture and pore geometry information.Because ultimately such small-scale SNMR-PP setups are intended for a mobile application,it is necessary to develop strategies that allow for speedy measurement progress and do not require noise cancellation protocols based on reference stations.Hence,we developed a new concentric figure-of-eight(cFOE)loop layout that combines the direction independence of a circular loop with the intrinsic noise cancellation properties of a classical FOE-loop.This approach significantly decreases the measurement time because suitable signal-to-noise ratios are reached much faster compared to a classical circular loop and will bring us one step further toward fast and non-invasive soil moisture mapping applications.

Frequency-Domain Wideband Acoustic Noise Cancellation System

When building an adaptive noise cancellation system for wideband acoustic signals, one can meet some difficulties in practical implementation of such a system. The major problem is related to the necessity of using real-time signal generation and processing. In this paper the active noise control system which utilizes adaptation in frequency domain is considered. It is shown that the proposed algorithms simplify practical implementation of a noise cancellation system. The results of computer simulations and prototype experiments show the effectiveness of the proposed methods. .

Practical Considerations for Implementing Adaptive Acoustic Noise Cancellation in Commercial Earbuds

Active noise cancellation has become a prominent feature in contemporary in-ear personal audio devices.However,due to constraints related to component arrangement,power consumption,and manufacturing costs,most commercial products utilize fixed-type controller systems as the basis for their active noise control algorithms.These systems offer robust performance and a straightforward structure,which is achievable with cost-effective digital signal processors.Nonetheless,a major drawback of fixed-type controllers is their inability to adapt to changes in acoustic transfer paths,such as variations in earpiece fitting conditions.Therefore,adaptive-type active noise control systems that employ adaptive digital filters are considered as the alternative.To address the increasing system complexity,design concepts and implementation strategies are discussed with respect to actual hardware limitations.To illustrate these considerations,a case study showcasing the implementation of a filtered-x least mean square-based active noise control algorithm is presented.A commercial evaluation board accommodating a low-cost,fixed-point digital signal processor is used to simplify operation and provide programming access.The earbuds are obtained from a commercial product designed for noise cancellation.This study underscores the importance of addressing hardware constraints when implementing adaptive active noise cancellation,providing valuable insights for real-world applications.

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.

Noise cancellation of a multi-reference full-wave magnetic resonance sounding signal based on a modified sigmoid variable step size least mean square algorithm

Nano-volt magnetic resonance sounding(MRS) signals are sufficiently weak so that during the actual measurement, they are affected by environmental electromagnetic noise, leading to inaccuracy of the extracted characteristic parameters and hindering effective inverse interpretation. Considering the complexity and non-homogeneous spatial distribution of environmental noise and based on the theory of adaptive noise cancellation, a model system for noise cancellation using multi-reference coils was constructed to receive MRS signals. The feasibility of this system with theoretical calculation and experiments was analyzed and a modified sigmoid variable step size least mean square(SVSLMS) algorithm for noise cancellation was presented. The simulation results show that, the multi-reference coil method performs better than the single one on both signal-to-noise ratio(SNR) improvement and signal waveform optimization after filtering, under the condition of different noise correlations in the reference coils and primary detecting coils and different SNRs. In particular, when the noise correlation is poor and the SNR<0, the SNR can be improved by more than 8 dB after filtering with multi-reference coils. And the average fitting errors for initial amplitude and relaxation time are within 5%. Compared with the normalized least mean square(NLMS) algorithm and multichannel Wiener filter and processing field test data, the effectiveness of the proposed method is verified.

Multi-channel differencing adaptive noise cancellation with multi-kernel method

Although a various of existing techniques are able to improve the performance of detection of the weak interesting sig- nal, how to adaptively and efficiently attenuate the intricate noises especially in the case of no available reference noise signal is still the bottleneck to be overcome. According to the characteristics of sonar arrays, a multi-channel differencing method is presented to provide the prerequisite reference noise. However, the ingre- dient of obtained reference noise is too complicated to be used to effectively reduce the interference noise only using the clas- sical linear cancellation methods. Hence, a novel adaptive noise cancellation method based on the multi-kernel normalized least- mean-square algorithm consisting of weighted linear and Gaussian kernel functions is proposed, which allows to simultaneously con- sider the cancellation of linear and nonlinear components in the reference noise. The simulation results demonstrate that the out- put signal-to-noise ratio （SNR） of the novel multi-kernel adaptive filtering method outperforms the conventional linear normalized least-mean-square method and the mono-kernel normalized least- mean-square method using the realistic noise data measured in the lake experiment.

Time-shared channel identification for adaptive noise cancellation in breath sound extraction

Noise artifacts are one of the key obstacles in applying continuous monitoring and computer-assisted analysis of lung sounds. Traditional adaptive noise cancellation (ANC) methodologies work reasonably well when signal and noise are stationary and independent. Clinical lung sound auscultation encounters an acoustic environment in which breath sounds are not stationary and often correlate with noise. Consequendy, capability of ANC becomes significantly compromised. This paper introduces a new methodology for extracting authentic lung sounds from noise-corrupted measurements. Unlike traditional noise cancellation methods that rely on either frequency band separation or signal/noise independence to achieve noise reduction, this methodology combines the traditional noise canceling methods with the unique feature of time-split stages in breathing sounds. By employing a multi-sensor system, the method first employs a high-pass filter to eliminate the off-band noise, and then performs time-shared blind identification and noise cancellation with recursion from breathing cycle to cycle. Since no frequency separation or signal/noise independence is required, this method potentially has a robust and reliable capability of noise reduction, complementing the traditional methods.

A new method of lung sounds filtering using modulated least mean square—Adaptive noise cancellation

Advanced processing of lung sound (LS) recording is a significant means to separate heart sounds (HS) and combined low frequency noise from instruments (NI), with saving its characteristics. This paper proposes a new method of LS filtering which separates HS and NI simultaneously. It focuses on the application of least mean squares (LMS) algorithm with adaptive noise cancelling (ANC) technique. The second step of the new method is to modulate the reference input r1(n) of LMS-ANC to acquiesce combining HS and NI signals. The obtained signal is removed from primary signal (original lung sound recording-LS). The original signal is recorded from subjects and derived HS from it and it is modified by a band pass filter. NI is simulated by generating approximately periodic white gaussian noise (WGN) signal. The LMS-ANC designed algorithm is controlled in order to determine the optimum values of the order L and the coefficient convergence μ. The output results are measured using power special density (PSD), which has shown the effectiveness of our suggested method. The result also has shown visual difference PSD (to) normal and abnormal LS recording. The results show that the method is a good technique for heart sound and noise reduction from lung sounds recordings simultaneously with saving LS characteristics.

Inductorless Ultra-Wide Band Front-End Chip Design with Noise Cancellation Technology for Wireless Communication Applications 10

为 3.14.8 GHz 的频率乐队在无线通讯使用的一个无引导者的极端宽的乐队(UWB ) 接收装置前端薄片图案被介绍。这 homodyne 接收装置主要由一个下面变换的混合器跟随的一个微分低噪音放大器(LNA ) 电路组成。有取消电阻器的噪音的建议 LNA 电路被连接到 CMOS 设备的身体减少底层热噪音。模拟和测量结果证明薄片能关于 0.5dB 减少前端噪音数字(NF ) 并且完成 19.4421.57 dB 和双边带 NF 的变换获得(CG ) 不到 7.8 dB。另外，输入第三顺序拦截点(IIP3 )-11 dBm，和输入秒顺序拦截点(IIP2 ) 是 49 dBm。在 TSMC 0.18 m 互补金属氧化物半导体技术制作了，这个薄片占据仅仅 0.167 mm2 并且驱散力量 59.2 mW。

Adaptive Noise Cancellation Algorithms Implemented onto FPGA-Based Electrical Impedance Tomography System

Electrical Impedance Tomography(EIT)as a non-invasive of electrical conductivity imaging method commonly employs the stationary-coefficient based filters(such as FFT)in order to remove the noise signal.In the practical applications,the stationary-coefficient based filters fail to remove the time-varying random noise which leads to the lack of impedance measurement sensitivity.In this paper,the implementation of adaptive noise cancellation(ANC)algorithms which are Least Mean Square(LMS)and Normalized Least Mean Square(NLMS)filters onto Field Programmable Gate Array(FPGA)-based EIT system is proposed in order to eliminate the time-varying random noise signal.The proposed method was evaluated through experimental studies with biomaterial phantom.The reconstructed EIT images with NLMS is better than the images with LMS by amplitude response AR=12.5%,position error PE=200%,resolution RES=33%,and shape deformation SD=66%.Moreover,the Analog-to-Digital Converter(ADC)performances of power spectral density(PSD)and the effective number of bit ENOB with NLMS is higher than the performances with LMS by SI=5.7%and ENOB=15.4%.The results showed that implementing ANC algorithms onto FPGA-based EIT system shows significantly more accurate image reconstruction as compared without ANC algorithms implementation.

A High Gain, Noise Cancelling 2515-4900 MHz CMOS LNA for China Mobile 5G Communication Application

With the development of the times,people’s requirements for communication technology are becoming higher and higher.4G communication technology has been unable to meet development needs,and 5G communication technology has emerged as the times require.This article proposes the design of a low-noise amplifier(LNA)that will be used in the 5G band of China Mobile Communications.A low noise amplifier for mobile 5G communication is designed based on Taiwan Semiconductor Manufacturing Company(TSMC)0.13μm Radio Frequency(RF)Complementary Metal Oxide Semiconductor(CMOS)process.The LNA employs self-cascode devices in current-reuse configuration to enable lower supply voltage operation without compromising the gain.This design uses an active feedback amplifier to achieve input impedance matching,avoiding the introduction of resistive negative feedback to reduce gain.A common source(CS)amplifier is used as the input of the low noise amplifier.In order to achieve the low power consumption of LNA,current reuse technology is used to reduce power consumption.Noise cancellation techniques are used to eliminate noise.The simulation results in a maximum power gain of 22.783,the reverse isolation(S12)less than-48.092 dB,noise figure(NF)less than 1.878 dB,minimum noise figure(NFmin)=1.203 dB,input return loss(S11)and output return loss(S22)are both less than-14.933 dB in the frequency range of 2515-4900 MHz.The proposed Ultra-wideband(UWB)LNA consumed 1.424 mW without buffer from a 1.2 V power supply.

Beamforming with the Generalized Sidelobe Cancellerfor Coherent Noise Attenuation in 3D Seismic Data

This paper presents a new approach for attenuating coherent noise in 3D seismic data. An adaptive beamforming with generalized sidelobe canceller (GSC) design methodology is utilized here as a general form of linearly constrained adaptive beamforming structure. It consists of a fixed beamformer, and a signal-blocking matrix in front of an unconstrained adaptive beamformer.Considerationf of the complexity of the geometry for 3D seismic survey, the 3D beamforming with GSC technique is developed with two key points: (1) sorting along azimuth sections to simplify the relationship between traveltime and offset from 3D to 2D, and (2) dynamic binning scheme to avoid the possible poor folding in some azimuth sections. Both simulation result and real data example show that the newly developed 3D beamforming with GSC yields more credible results at a relative low cost, sufficient stability and good resolution.

Least mean square error difference minimum criterion for adaptive chaotic noise canceller

The least mean square error difference （LMS-ED） minimum criterion for an adaptive chaotic noise canceller is proposed in this paper. Different from traditional least mean square error minimum criterion in which the error is uncorrelated with the input vector, the proposed LMS-ED minimum criterion tries to minimize the correlation between the error difference and input vector difference. The novel adaptive LMS-ED algorithm is then derived to update the weights of adaptive noise canceller. A comparison between cancelling performances of adaptive least mean square （LMS）, normalized LMS （NLMS） and proposed LMS-ED algorithms is simulated by using three kinds of chaotic noises. The simulation results clearly show that the proposed algorithm outperforms the LMS and NLMS algorithms in achieving small values of steady-state excess mean square error. Moreover, the computational complexity of the proposed LMS-ED algorithm is the same as that of the standard LMS algorithms.

A 9 - 10.6 GHz Microstrip Antenna—UWB Low Noise Amplifier with Differential Noise Canceling Technique for IoT Applications

An ultra-wide band (UWB) receiver front-end that operates at the UWB frequency range, starting from 9 GHz - 10.6 GHz is proposed in this paper. The proposed system consists of an off-chip microstrip antenna and CMOS differential low noise amplifier with a differential noise canceling (DNC) technique. The proposed antenna is trapezoidal dipole shaped with balun and printed on a low-cost FR4 substrate with dimensions 10 × 10 × 0.8 mm3. The balun circuit integrated with the ground antenna to improve the antenna impedance matching. Noise canceling is obtained by using a differential block with each stage having 2 amplifiers that generate differential signals, subtracted to improve total noise performance. The proposed DNC block improves NF by 50% while increasing total power consumption with only 0.1 Mw. The differential CMOS cascode LNA with DNC block is implemented using UMC 0.13 μm CMOS process, exhibits a flat gain of 19 dB, maximum noise figure of 2.75 dB, 1 dB compression point &#8722;16 dBm and 3rd order intercept point (IIP3) &#8722;10 dBm. The proposed system has total DC power consumption of 2.8 mW at 1.2 V power supply.

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.

Design and analysis on four stage SiGe HBT low noise amplifier

Focusing on the linearity shortcoming on a bipolar low noise amplifier(LNA),a new 6 ~14GHz four stage SiGe HBT LNA is proposed.This amplifier adopts a method of gain allocation on multiple stages to avoid the limitation on linearity especially with the addition of negative gain on the third stage.To realize gain flatness,extra zero is introduced to compensate the gain roll-off formed by pole,and local shunt-shunt negative feedback is used to widen the bandwidth as well as optimize circuit' s noise.Simulated results have shown that in 6 ~14GHz,this circuit achieves noise figure(NF) less than 3dB,gain of 17.8dB(+0.2dB),input and output reflection parameters of less than- 10 dB,and the K factor is above 1.15.

Nonparametric VSS-APA based on precise background noise power estimate

The adaptive algorithm used for echo cancellation(EC) system needs to provide 1) low misadjustment and 2) high convergence rate. The affine projection algorithm(APA) is a better alternative than normalized least mean square(NLMS) algorithm in EC applications where the input signal is highly correlated. Since the APA with a constant step-size has to make compromise between the performance criteria 1) and 2), a variable step-size APA(VSS-APA) provides a more reliable solution. A nonparametric VSS-APA(NPVSS-APA) is proposed by recovering the background noise within the error signal instead of cancelling the a posteriori errors. The most problematic term of its variable step-size formula is the value of background noise power(BNP). The power difference between the desired signal and output signal, which equals the power of error signal statistically, has been considered the BNP estimate in a rough manner. Considering that the error signal consists of background noise and misalignment noise, a precise BNP estimate is achieved by multiplying the rough estimate with a corrective factor. After the analysis on the power ratio of misalignment noise to background noise of APA, the corrective factor is formulated depending on the projection order and the latest value of variable step-size. The new algorithm which does not require any a priori knowledge of EC environment has the advantage of easier controllability in practical application. The simulation results in the EC context indicate the accuracy of the proposed BNP estimate and the more effective behavior of the proposed algorithm compared with other versions of APA class.