一种应用于心磁噪声抑制的选择性平均方法研究

在心磁信号探测中, 抑制环境噪声是提取心磁信号的关键. 为了提高心磁信号的信噪比, 信号平均得到了广泛地使用. 然而, 由于局部干扰噪声的存在, 对整段数据进行平均的传统方法不可避免地会带来心磁信号的失真. 本文通过采取模版匹配的方式, 提出了一种选择性平均方法. 结果显示, 本方法能有效剔除带有低频波动、脉冲毛刺等干扰的数据段, 获取高质量的平均心磁信号. 关键词： 心磁 信号平均 噪声抑制 信噪比     

互补型自适应滤波器在心磁信号处理中的应用

将心磁信号从干扰噪声中加以提取并有效地消除噪声干扰是心磁信号处理中尤为重要的环节 .从改进算法的角度出发，提出互补型自适应滤波器结构以实现心磁信号的消噪处理.该滤波器针对心磁这类非平稳信号进行设计，有效地解决了常规自适应滤波器应用于心磁信号处理时收敛速度和稳态误差的矛盾.通过仿真实验和心磁实验结果表明，该算法能有效地消除心磁信号的背景噪声和工频干扰噪声.同时该算法也可用于其他非平稳信号的消噪处理. 关键词： 自适应滤波 心磁图 最小均方误差     

改进维纳滤波器及其在目标方位估计中的应用

针对复杂的水声环境以及信噪比较低的目标信号导致方位估计性能较差的问题,本文提出了一种基于改进维纳滤波器和波束形成器的方位估计方法,该方法能够抑制噪声,提高目标方位估计性能。首先利用改进维纳滤波器抑制各通道接收数据中的噪声,提高输出信噪比。在此基础上,将改进维纳滤波器的输出通过波束形成器,获得目标的方位估计。改进维纳滤波器能够通过调整滤波器参数,控制滤波器的噪声抑制能力和信号失真。因此,针对不同的波束形成器对信号失真的敏感程度不同,可以通过调节改进维纳滤波器的参数,获得噪声抑制与信号失真之间的最佳折中,从而提高输出信噪比,降低目标方位估计的信噪比门限和均方根误差。仿真和实验结果验证了本文方法。      

基于心磁信号的心脏电流偶极子阵列成像及相关性质的研究

超导量子干涉器（SQUID）能探测到微弱的心脏磁场信号. 通过对所得的心磁信号进行分析,可为许多心脏疾病的诊断提供依据. 利用心磁信号,采用极小范数最小二乘法（MNLS）对心脏的电流偶极子阵列进行重建,从而实现了对心脏内部等效电流源的成像. 在使用MNLS进行电流偶极子阵列反演重建的过程中,反演所需的心磁信号,分别由单电流偶极子和电流多极子作为激发源模拟得到,以及由SQUID实际测量得到. 同时,对不同心磁信号反演得到的电流偶极子的分布规律进行了分析. 此外,还给模拟的人体外心磁信号施加了均匀噪声和随机噪声,研究不同信噪比的均匀噪声和随机噪声对电流偶极子阵列重建的影响.     

小波变换在心磁信号处理中的应用

噪声的消除一直是微弱信号检测和处理中尤为重要的一个环节.从小波变换的角度出发，利用了小波变换在时、频两域都具有表征信号局部特征的能力，对心磁信号这种典型的微弱信号进行了消噪处理.实验中的心磁数据是单通道高温超导量子干涉磁强计测得.理论分析和实验结果表明，这种方法能有效地提高输出信噪比，同时也适合于其他非平稳信号的消噪. 关键词： 小波变换 心磁 消噪     

基于心磁信号的心脏电流偶极子阵列成像及相关性质的研究

超导量子干涉器（SQUID）能探测到微弱的心脏磁场信号. 通过对所得的心磁信号进行分析,可为许多心脏疾病的诊断提供依据. 利用心磁信号,采用极小范数最小二乘法（MNLS）对心脏的电流偶极子阵列进行重建,从而实现了对心脏内部等效电流源的成像. 在使用MNLS进行电流偶极子阵列反演重建的过程中,反演所需的心磁信号,分别由单电流偶极子和电流多极子作为激发源模拟得到,以及由SQUID实际测量得到. 同时,对不同心磁信号反演得到的电流偶极子的分布规律进行了分析. 此外,还给模拟的人体外心磁信号施加了均匀噪声和随机噪声,研究不同信噪比的均匀噪声和随机噪声对电流偶极子阵列重建的影响. 关键词： 心磁信号 超导量子干涉器 电流偶极子阵列重建 极小范数最小二乘法     

差分传声器阵列低频特性优化研究*

利用传声器阵列差分信号处理可以获得指向性波束,可用于定向声捡拾或环绕声捡拾,但该处理方式产生了高通滤波作用,降低了信号低频段的信噪比,将影响输出音质。本文提出了一种时变补偿滤波器,在补偿差分信号低频能量的同时避免了引入过多噪声。仿真分析中,信号与噪声分别为chirp信号、高斯白噪声,信噪比为50 d B,时变补偿滤波器较常规补偿方式信噪比提高了约6 d B。音质主观评测结果表明,采用本方法进行低频补偿,可以获得更好的低频音质。     

射频SQUID心磁图数据自适应滤波研究

研究了滤除50Hz工频干扰的几种自适应算法，并应用于射频超导量子干涉仪（SQUID）心 磁图仪采集的心磁数据50Hz滤波中.对算法的性能进行了计算机仿真比较.结果表明，带50 Hz干扰的SQUID心磁信号通过自适应噪声对消法，干扰得到了很好的抑制. 关键词： SQUID 心磁图 自适应滤波 噪声消除     

基于形态滤波的心电信号去除基线漂移方法

去除基线漂移是心电信号预处理过程中的重要一步,常见方法具有计算量大、结果不佳等缺陷.本文运用形态学理论,结合心电信号特征,提出了基于形态学的心电信号基线漂移去除方法.该方法采用不同形状及尺寸的结构元素设计了两级形态学滤波器,分别对信号进行开闭、闭开级联组合运算.经验证,提出的方法能很好保持心电信号的特征形态,提高了信噪比,减小了均方差,有效去除了基线漂移噪声.     

应用于助听器反馈抑制的信噪比自适应滤波算法*

针对基于自适应滤波器的助听器反馈抑制系统,本文提出了一种基于信噪比的归一化最小均方误差算法,采用最小值统计法估计误差信号的噪声分量,从而计算出误差信号的信噪比来计算自适应滤波系数的更新步长。当误差信号信噪比越高,语音占主要成分,信号的相关性越强,此时将滤波器的更新步长控制在较小值,减小滤波器的失调量。当信噪比越低时,噪声占主要成分,信号的相关性相对较弱,更新步长取较大值,加快滤波器的收敛速度。在仿真实验中,本文提出的基于信噪比的归一化最小均方误差算法相较于传统算法在平均稳态失调量和稳态失调范围上分别低1dB和2dB,其最大稳态增益提高了4dB,同时具有更快的稳态收敛速度,验证了本文提出算法的有效性。     

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.     

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.     

用于心脏电活动成像的空间滤波器输出噪声抑制方法

利用人体表面测量的心脏磁场数据无创成像心脏电活动,需要解决的关键问题是提高其重建分布电流源偶极矩强度的分辨率.本文在最小方差波束成形(MVB)方法的基础上,提出了一种可抑制空间滤波器输出噪声功率增益(SONG)的波束成形方法,目的是通过构造一种新的滤波器权矩阵,约束空间滤波器的输出噪声功率增益,提高重建分布电流源偶极矩强度的分辨率,即分布电流源空间谱估计的源分辨能力,从而增强心脏电活动磁成像的分辨率.文中给出了电流源重建的理论分析和仿真结果;比较了该方法与MVB方法的差别;并给出了两个健康人36通道心脏磁场数据的电活动成像.结果表明,SONG方法分辨电流源的能力较强,能够观察到心脏电磁场信号R峰时刻健康人的心室电活动较强,心房电活动较弱等特征.     

滤波器与随机共振结合检测微弱信号

基于双稳随机共振系统及滤波器的不同特性,本文提出了一种将两者结合起来检测微弱周期信号的方法,先用自适应前置滤波器对输入的弱周期信号及噪声进行滤波,再使其通过双稳随机共振系统,进而检测出弱信号。对比只有双稳随机共振的系统,仿真结果表明此时的输出信号中待测信号频谱幅度得到了很大的提高,且周围的干扰信号也得到了明显的削弱,即两者的结合使用可以更好的检测出微弱信号,这对强噪声背景下的信号检测有很强的实用性。     

Experimental evaluation of leaky least-mean-square algorithms for active noise reduction in communication headsets

An adaptive leaky normalized least-mean-square (NLMS) algorithm has been developed to optimize stability and performance of active noise cancellation systems. The research addresses LMS filter performance issues related to insufficient excitation, nonstationary noise fields, and time-varying signal-to-noise ratio. The adaptive leaky NLMS algorithm is based on a Lyapunov tuning approach in which three candidate algorithms, each of which is a function of the instantaneous measured reference input, measurement noise variance, and filter length, are shown to provide varying degrees of tradeoff between stability and noise reduction performance. Each algorithm is evaluated experimentally for reduction of low frequency noise in communication headsets, and stability and noise reduction performance are compared with that of traditional NLMS and fixed-leakage NLMS algorithms. Acoustic measurements are made in a specially designed acoustic test cell which is based on the original work of Ryan et al. ["Enclosure for low frequency assessment of active noise reducing circumaural headsets and hearing protection," Can. Acoust. 21, 19-20 (1993)] and which provides a highly controlled and uniform acoustic environment. The stability and performance of the active noise reduction system, including a prototype communication headset, are investigated for a variety of noise sources ranging from stationary tonal noise to highly nonstationary measured F-16 aircraft noise over a 20 dB dynamic range. Results demonstrate significant improvements in stability of Lyapunov-tuned LMS algorithms over traditional leaky or nonleaky normalized algorithms, while providing noise reduction performance equivalent to that of the NLMS algorithm for idealized noise fields.     

A Novel Filter Scheme of Data Processing for SQUID-Based Magnetocardiogram

We present a new filter scheme for magnetocardiogram （MCG） signal processing based on the quasi-periodic characteristic of the signals. The key points of this scheme are to determine the exact numbers of data points in each cardiac cycle by using electrocardiogram （ECG） data acquired simultaneously with the MCG signal and to normalize the MCG data sequence in each cycle into an identical length. Compared with conventional filters, the scheme has the advantage of more powerful noise suppression with less signal distortion. The desire for having high quality output signals from raw MCG data acquired in a simple shielded room or even in unshielded environment may be realized with the scheme.     

Adaptive filter for unwrapping noisy phase image in phase-stepping interferometry

An adaptive filter for preprocessing wrapped phase image with high noise content has been developed. The window size of this median filter is adjustable according to its location in the noisy phase image. This size-adjustable median filter has not only high noise-rejection ability, but also both good phase-jump identification and image-detail preservation properties. Phase unwrapping can then be done to recover the real phase image without the hampering influence of noise, especially the noise near the phase jumps. Both numerical simulation and experimental results used to examine the effectiveness of this adaptive filter are presented.     

A synthetic optically pumped gradiometer for magnetocardiography measurements

Magnetocardiography(MCG)measurement is important for investigating the cardiac biological activities.Traditionally,the extremely weak MCG signal was detected by using superconducting quantum interference devices(SQUIDs).As a room-temperature magnetic-field sensor,optically pumped magnetometer(OPM)has shown to have comparable sensitivity to that of SQUIDs,which is very suitable for biomagnetic measurements.In this paper,a synthetic gradiometer was constructed by using two OPMs under spin-exchange relaxation-free(SERF)conditions within a moderate magnetically shielded room(MSR).The magnetic noise of the OPM was measured to less than 70 fT/Hz1/2.Under a baseline of 100 mm,noise cancellation of about 30 dB was achieved.MCG was successfully measured with a signal to noise ratio(SNR)of about 37 dB.The synthetic gradiometer technique was very effective to suppress the residual environmental fields,demonstrating the OPM gradiometer technique for highly cost-effective biomagnetic measurements.