A normalized data-reusing least-mean-square algorithm of noise cancellation for magnetocardiography

An adaptive filter based on Data-Reusing Least-Mean-Square algorithm has been proposed and applied in magnetocardiography (MCG) to suppress ambient noise, Numerical simulation studies indicate that the adaptive filter is a powerful noise suppresser for correlated interferences, especially for those with amplitude changing and time delay.Also the filter has a wide frequency bandwidth. With this filter, the signal-to-noise ratio of an MCG is improved to the intrinsic noise level, The periodic average method for further improvement of the noise level in MCG is also discussed.     

自适应中值-加权均值混合滤波器

为了去除图像中混入的脉冲噪声和高斯噪声,提出了一种基于自适应中值滤波和自适应加权均值滤波的混合滤波方法。该方法先将图像分为若干区域,并对每个区域进行噪声检测以实现两类噪声的分离,然后再分别采用自适应中值滤波和自适应加权均值滤波将分离出的脉冲噪声和高斯噪声去除。对这种新方法进行了计算机模拟实验。结果表明:新方法较前人提及的三种混合滤波方法具有更优的滤波性能,在有效抑制混合噪声的同时能很好地保护图像中的细节,为消除图像中的混合噪声提供了一种有效的途径。     

基于小波变换的图像混合噪声自适应滤除算法

为同时滤除图像中的椒盐噪声和高斯噪声,提出了一种基于小波变换的混合噪声自适应滤除算法,该算法首先采用中值滤波去除椒盐噪声,然后借助边缘检测算子区将图像为分边缘与非边缘区域,进一步对非边缘区域引入改进的均值滤波器,有效削弱高斯噪声的同时保护图像边缘细节,既初步削弱高斯噪声又保护了边缘,最后采用改进的小波阈值滤波算法,对不同的小波系数采用不同的阈值函数,通过线性回归得到各最优阈值关系式。实验结果表明,该混合噪声自适应滤除算法能有效滤除椒盐噪声和高斯噪声,在图像主观质量和客观质量上均取得了较好的效果,能提高去噪图像峰值信噪比0.5~2.0 dB。     

Decision-based adaptive morphological filter for fixed-value impulse noise removal

A novel adaptive switching morphological filter for removing fixed-value impulse noise is proposed. The proposed filter firstly identifies noise pixels using the two-stage morphological noise detector, in which the initial noise detection is used to identify the noise candidates based on the morphological gradients and the refined noise detection based on the combined conditional morphological operators is adopted to further classify the noise candidates as the noise pixels or noise-free pixels. Then the detected noise pixels are removed by the adaptive morphological filter using the conditional rank-order morphological operators while the noise-free pixels are left unaltered. Extensive simulations show that the proposed filter outperforms a number of existing switching-based filters because of its excellent performance in terms of noise detection and image restoration.     

Influence of quantization error on the performance of an adaptive transversal filter

We report on the results of a theoretical analysis of the influence of quantization error on the performance of an adaptive transversal filter minimizing the root-mean-square error by means of a gradient least-mean-square algorithm. An expression for the covariance matrix of weight coefficients is defined. The dependence of the output excess noise power on the adaptive system parameters is analyzed.Lobachevskii State University, Nizhny Novgorod. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 38, No. 6, pp. 566–576, June, 1995.     

数字滤波在心磁噪声抑制中的应用

提出了一种基于数据重置最小均方算法的自适应数字滤波器, 并将其应用于抑制心磁信号的背景噪声. 数值模拟结果表明该滤波器对于相关噪声,尤其是有幅值变化和时间延迟的情况, 有很强的抑制效果. 该滤波器有很宽的带宽.利用它可以使心磁信号的信噪比提高到器件的本征噪声水平. 利用周期平均的方法进一步提高信噪比, 对滤波前后心磁信号的频谱进行了分析.     

Flexible polarization demultiplexing method based on an adaptive process noise covariance Kalman filter

A flexible polarization demultiplexing method based on an adaptive Kalman filter(AKF) is proposed in which the process noise covariance has been estimated adaptively. The proposed method may significantly improve the adaptive capability of an extended Kalman filter(EKF) by adaptively estimating the unknown process noise covariance. Compared to the conventional EKF, the proposed method can avoid the tedious and time consuming parameter-by-parameter tuning operations. The effectiveness of this method is confirmed experimentally in 128 Gb/s 16 QAM polarization-division-multiplexing(PDM) coherent optical transmission systems. The results illustrate that our proposed AKF has a better tracking accuracy and a faster convergence(about 4 times quicker)compared to a conventional algorithm with optimal process noise covariance.     

Multi-parameter identification from scalar time series generated by a Malkus-Lorenz water wheel

We address the issue of multi-parameter estimation from scalar outputs of chaotic systems, using the dynamics of a Malkus water wheel and simulations of the corresponding Lorenz-equations model as an example. We discuss and compare two estimators: one is based on a globally convergent adaptive observer and the second is an extended Kalman filter (EKF). Both estimators can identify all three unknown parameters of the model. We find that the estimated parameter values are in agreement with those obtained from direct measurements on the experimental system. In addition, we explore the question of how to distinguish the impact of noise from those of model imperfections by investigating a model generalization and the use of uncertainty estimates provided by the extended Kalman filter. Although we are able to exclude asymmetric inflow as a possible unmodeled effect, our results indicate that the Lorenz-equations do not perfectly describe the water wheel dynamics.     

Asymmetry of masking between noise and iterated rippled noise: evidence for time-interval processing in the auditory system.

This study describes the masking asymmetry between noise and iterated rippled noise (IRN) as a function of spectral region and the IRN delay. Masking asymmetry refers to the fact that noise masks IRN much more effectively than IRN masks noise, even when the stimuli occupy the same spectral region. Detection thresholds for IRN masked by noise and for noise masked by IRN were measured with an adaptive two-alternative, forced choice (2AFC) procedure with signal level as the adaptive parameter. Masker level was randomly varied within a 10-dB range in order to reduce the salience of loudness as a cue for detection. The stimuli were filtered into frequency bands, 2.2-kHz wide, with lower cutoff frequencies ranging from 0.8 to 6.4 kHz. IRN was generated with 16 iterations and with varying delays. The reciprocal of the delay was 16, 32, 64, or 128 Hz. When the reciprocal of the IRN delay was within the pitch range, i.e., above 30 Hz, there was a substantial masking asymmetry between IRN and noise for all filter cutoff frequencies; threshold for IRN masked by noise was about 10 dB larger than threshold for noise masked by IRN. For the 16-Hz IRN, the masking asymmetry decreased progressively with increasing filter cutoff frequency, from about 9 dB for the lowest cutoff frequency to less than 1 dB for the highest cutoff frequency. This suggests that masking asymmetry may be determined by different cues for delays within and below the pitch range. The fact that masking asymmetry exists for conditions that combine very long IRN delays with very high filter cutoff frequencies means that it is unlikely that models based on the excitation patterns of the stimuli would be successful in explaining the threshold data. A range of time-domain models of auditory processing that focus on the time intervals in phase-locked neural activity patterns is reviewed. Most of these models were successful in accounting for the basic masking asymmetry between IRN and noise for conditions within the pitch range, and one of the models produced an exceptionally good fit to the data.     

基于改进雁群PSO算法的模糊自适应扩展卡尔曼滤波的SLAM算法

针对扩展卡尔曼滤波同时定位与地图创建算法中难以建立准确的先验噪声模型的问题, 提出一种基于改进雁群粒子群算法的模糊自适应卡尔曼滤波算法. 利用分数阶微积分改进粒子进化速度, 利用混沌来改进粒子的初始化和发生早熟时的处理. 改进后的雁群粒子群算法在收敛速度与避免早熟方面有了很大改进, 并将改进的雁群粒子群算法用于模糊自适应扩展卡尔曼滤波同时定位与地图创建算法的训练, 并与用雁群粒子群算法训练的模糊自适应扩展卡尔曼滤波同时定位与地图创建算法进行对比, 其在定位与构图方面有很大的提高. 关键词： 同时定位与地图创建 雁群粒子群算法 分数阶微积分 混沌     

A digital filtering scheme for SQUID based magnetocardiography

Considering the properties of slow change and quasi-periodicity of magnetocardiography (MCG) signal, we use an integrated technique of adaptive and low-pass filtering in dealing with two-channel MCG data measured by high $T_{\rm c}$ SQUIDs. The adaptive filter in the time domain is based on a noise feedback normalized least-mean-square (NLMS) algorithm, and the low-pass filter with a cutoff at 100Hz in the frequency domain characterized by Gaussian functions is combined with a notch at the power line frequency. In this way, both relevant and irrelevant noises in original MCG data are largely eliminated. The method may also be useful for other slowly varying quasi-periodical signals.     

Generation of a squeezed state at 1.55 μm with periodically poled LiNbO₃

We report on the generation of a squeezing vacuum at 1.55 μm using an optical parametric amplifier based on periodically poled LiNbO 3.Using three specifically designed narrow linewidth mode cleaners as the spatial mode and noise filter of the laser at 1.55 μm and 775 nm,the squeezed vacuum of up to 3.0 dB below the shot noise level at 1.55 μm is experimentally obtained.This system is compatible with standard telecommunication optical fibers,and will be useful for continuous variable long-distance quantum communication and distributed quantum computing.     

基于改进遗传算法优化的形态学修正TOP-HAT滤波器设计方法

针对红外序列图像中运动弱小点目标的检测问题,设计了一种基于改进遗传算法优化的修正Top-Hat形态学滤波器算子。其中,优化的修正Top-Hat形态学滤波器可以很好地抑制背景和噪声的影响;改进遗传算法采用新的区间离散化编码和自适应的主次式交叉与变异算子,通过优化搜索全局空间得到的形态学滤波器参量具有较好的滤波性及时效性。并且针对不同信噪比的点目标检测建立了自适应门限。实测数据的处理结果表明:在虚警概率小于5%情况下,优化的修正Top-Hat形态学滤波器算子对信噪比约为2的复杂图像检测概率大于等于70%,与固定结构元素的Top-Hat形态学滤波器相比检测概率提高了近10%,与用经典遗传算法训练的传统Top-Hat形态学滤波器相比检测概率提高了4%。     

Rician noise reduction in magnetic resonance images using adaptive non-local mean and guided image filtering

This paper proposes a Rician noise reduction method for magnetic resonance (MR) images. The proposed method is based on adaptive non-local mean and guided image filtering techniques. In the first phase, a guidance image is obtained from the noisy image through an adaptive non-local mean filter. Sobel operators are applied to compute the strength of edges which is further used to control the spread of the kernel in non-local mean filtering. In the second phase, the noisy and the guidance images are provided to the guided image filter as input to restore the noise-free image. The improved performance of the proposed method is investigated using the simulated and real data sets of MR images. Its performance is also compared with the previously proposed state-of-the art methods. Comparative analysis demonstrates the superiority of the proposed scheme over the existing approaches.     

头部旋转运动下自适应非接触鲁棒性心率检测方法

基于人脸视频的生理信号检测面临的主要挑战是运动伪影噪声.针对受试者头部刚性旋转运动引起的伪影噪声,本文提出利用头部运动信息构建自适应滤波器的非接触式心率检测方法.该方法利用人脸二维和三维的特征点计算受试者运动中头部的偏航和俯仰欧拉角度,并将其作为调控过程噪声协方差的信号质量指数,进而构建了自适应Kalman滤波器,实现了稳健的心率估计.实验结果表明:本文提出的方法可有效抑制头部刚性旋转运动引起的噪声,平均绝对误差为2.22 beat/min,均方根误差为2.76 beat/min,与现有方法相比准确度分别提升9%与24.6%,具有统计显著性.本文提出的头部旋转角度自适应非接触鲁棒性心率检测方法在自发运动的真实场景下能有效提升检测的准确性,扩大了成像式光电容积描记技术在视频健康监测领域的使用场景.     

Random-valued impulse noise removal by the adaptive switching median detectors and detail-preserving regularization

This paper firstly proposes an adaptive non-local switching median filter. Then, a two-phase scheme is presented to remove the random-valued impulse noise. In the first phase, the adaptive switching median filter or the adaptive non-local switching median filter is used to identify the pixels which are likely to be the noise candidates. In the second phase, only the noise candidates’ values are restored by a detail-preserving regularization method. Simulation results show that the proposed method is significantly superior to some of the state-of-the-art methods.     

Generation of a squeezed state at 1.55 μ with periodically poled LiNbO3

We report on the generation of a squeezing vacuum at 1.55 μm using an optical parametric amplifier based on periodically poled LiNbO₃. Using three specifically designed narrow linewidth mode cleaners as the spatial mode and noise filter of the laser at 1.55 μm and 775 nm, the squeezed vacuum of up to 3.0 dB below the shot noise level at 1.55 μm is experimentally obtained. This system is compatible with standard telecommunication optical fibers, and will be useful for continuous variable long-distance quantum communication and distributed quantum computing.     

基于NLMS自适应滤波的近红外光谱去噪处理方法研究

为了去除直接采集的近红外(NIR)光谱中含有的噪声,将归一化最小均方(NLMS)自适应滤波方法引入到NIR光谱去噪领域中。以51份土壤样品的NIR光谱为研究对象,探讨NLMS自适应滤波方法在NIR光谱预处理中的应用,并将处理后的结果与土壤中有机质的含量相关联,建立模型。结果表明,通过NLMS自适应滤波去噪后的光谱,预测集的相关系数r由处理前的0.8284提高至0.9654,预测均方根误差(RMSEP)由处理前的0.3385降至0.1606。由此可见,NLMS自适应滤波对NIR光谱的去噪有显著效果,可以有效地提高光谱的分析精度和模型的稳健性,为NIR光谱的预处理提供了一种新方法。     

基于干扰对消的红外焦平面非均匀性校正算法

红外焦平面器件的非均匀性产生机理复杂,难以准确拟合探测元响应曲线。提出了一种基于相关干扰抵消的非均匀性校正算法,以预先采集到的一帧黑体面源图像做为自适应干扰对消器的参考输入图像,自适应滤波器由参考输入图像迭代计算出待校正红外图像的空间噪声的最佳估计,实现从空间噪声中提取真实图像信号。自适应滤波算法采用变步长最小均方误差算法,减少了算法的运算量,提高了算法的收敛速度。理论分析以及针对实际红外图像的仿真结果表明,提出的算法校正效果好,收敛速度快,更易于工程实现。     

基于简化模型与自适应滤波的车载SINS静基座快速对准

为了实现捷联惯性导航系统(Strap-down Inertial Navigation System,SINS)快速初始对准,根据已有可观测性分析结果,通过理论分析和计算得到了扩展观测量时初始对准系统最优可观测状态量组合,在此基础上简化了对准模型,建立了新的系统方程。针对载车发动机启动或其他情况导致系统噪声无法精确统计,提出了运用基于强跟踪滤波原理的自适应卡尔曼滤波(Kalman Filter,KF)算法抑制滤波发散,加快收敛速度。仿真结果表明运用简化模型和自适应滤波在系统噪声不匹配时具有更快的收敛速度和更高的对准精度,车载实验结果也表明运用简化模型和自适应滤波可以实现快速对准。