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     

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.     

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     

解相关自适应滤波在光纤陀螺信号处理中的应用

在分析光纤陀螺噪声特性的基础上,研究了减少光纤陀螺信号随机漂移的方法,采用解相关变步长LMS算法,对光纤陀螺信号进行滤波,并同LMS滤波算法进行了比较,这种算法具有更快的收敛速度。实验结果表明,解相关变步长LMS算法对于抑制光纤陀螺中的随机漂移、提高信噪比具有良好的效果。     

基于相空间邻域的混沌时间序列自适应预测滤波器(Ⅱ)非线性自适应滤波

根据相空间重构理论、最小均方误差准则和最陡下降原理，提出了一种基于相空间邻域的非线性自适应滤波算法.实验结果表明：这种非线性自适应预测滤波器能够有效预测一些混沌序列，在某种程度上具有抗噪声的能力. 关键词： 混沌时间序列 重构矢量 最小均方误差准则 非线性自适应预测     

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。     

高Tcrf SQUID梯度计及其在心磁图测量中的应用

我们用两套ＨＴｃｒｆＳＱＵＩＤ组成一阶梯度计,在无屏蔽条件下,进行了心磁图测量。实验结果表明,在利用了梯度计消除环境噪声,再通过平均、数字滤波等方法进一步提高信噪比后,我们测得的心磁图中,可以清楚地看到Ｐ、Ｑ、Ｒ、Ｓ、Ｔ等各个波,其信噪比达到１２０,已可满足实用的要求。     

声光自适应信号处理技术在扩频通信中的应用

研究了声光滤波的工作原理,用布拉格器件作模拟抽头延迟线完成横向滤波。讨论了LMS自适应滤波的基本方法,给出了声光自适应LMS滤波的实现方法并用于扩频通信的窄带干扰抑制中。对扩频通信进行干扰抑制的滤波过程通常是一个自适应过程,采用声光自适应滤波技术,不仅能抑制窄带干扰,而且能提高系统的处理增益和分辨率。     

一种互补型自适应滤波最小均方法在SQUID测量的心磁信号中的应用

提出了一种互补型自适应滤波最小均方算法在SQUID测量的心磁信号中的应用，快的收敛速度和很好的跟踪能力通过根据最小均方原则在两个滤波器之间来回转换加权参量来实现     

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.     

An adaptive speech enhancement method for siren noise cancellation

Siren noises usually severely disturb the intelligibility of voice communication inside the cabs of police, paramedic and fire vehicles. It is often desired that such unwanted noise can be removed from the speech signal. In this paper, a new method is proposed to adaptively cancel siren noises and enhance speech signals. Based on the characteristics of siren noises, an anti-speech filter and a time delayer are employed in the single and dual channel noise cancellation systems to reduce the siren noises. Experiment results demonstrate that the effectiveness of the proposed method for canceling the siren noises and the performance of the enhanced speech signal is satisfying.     

On implementation of adaptive bilinear filters for nonlinear active noise control

In this technical note, the simplified diagonal-structure bilinear filtered-X least mean square (SDBFXLMS) and channel-reduced diagonal-structure bilinear filtered-X least mean square (CRDBFXLMS) algorithms are proposed. Computational complexity for each proposed algorithm is analyzed to show the significant computational reduction in comparison with the diagonal-structure bilinear FXLMS (DBFXLMS) algorithm. For L=15$L=15$ (memory length of the bilinear filter), P=2$P=2$ (the corresponding number of the diagonal channels for the SDBFXLMS algorithm is L+2P=19$L+2P=19$ and the corresponding number of the diagonal channels for the CRDBFXLMS algorithm is 2P=4)$2P=4)$, and M=64$M=64$ (memory length of the secondary path estimate), the SDBFXLMS algorithm achieves 45% and 40% reduction of multiplications and additions, respectively, while the CRDBFXLMS algorithm acquires 78% reduction of multiplications and 76% reduction of additions. Computer simulations validate the satisfied control performances of the proposed algorithms.     

改进的变步长自适应最小均方算法及其数字信号处理

针对紫外光通信中传统自适应最小均方（LMS）算法存在的不足,提出了一种新的变步长LMS(VSS-LMS)算法,利用MATLAB仿真验证了该算法的可行性,以TMS320VC5509为核心设计了数字信号处理（DSP）最小化硬件系统和VSS-LMS算法的软件流程,在硬件上实现了传统LMS算法和新的VSS-LMS算法的自适应滤波,并进行了对比分析,结果表明所提出的VSS-LMS算法具有较快的收敛速度和较小的稳态误差,这对紫外光通信接收系统的设计和优化具有一定的参考意义。     

基于自适应滤波器的大气湍流噪声抑制

为了解决大气湍流效应所引起的光无线通信系统中的衰落问题,建立了与大气湍流噪声及其它加性噪声有关的信号模型,实现了最大输出信噪比可提高3-20dB的匹配滤波器。根据最大似然比准则,推导了强度调制/直接探测(IM/DD)的光无线通信系统的最佳判决门限。采用自适应滤波器实现了对探测门限中所含的信号和湍流的统计值的预测,该自适应门限探测技术对大气湍流噪声有很好的抑制作用,在强湍流情况下,可降低系统的误码率到10-5以下。     

一种基于虚拟传感的无需误差传声器的自适应有源降噪方法*

该文基于虚拟传感技术引入了一种用于耳机的无需误差传声器的自适应有源降噪方法。该算法仅使用一个参考传声器实现了一种前馈和反馈自适应算法结合的有源降噪算法,提高了有源降噪稳定性,简化了耳机硬件结构。利用DSP平台实现了该文提出的方案,并通过实验验证了其良好的降噪性能和实用价值。     

The application of adaptive noise cancellation to pyroelectric detectors

This paper discusses the application of a signal processing technique known as Adaptive Noise Cancellation to the problem of reducing noise levels at the output of a pyroelectric detector. The detection system is considered in relation to self-modulating sources so that the input signals can be considered as pseudo-periodic. Two forms of adaptive processing, namely the Adaptive Line Enhancer and spike sequence input, are compared and contrasted, both methods are shown to improve signal-to-noise and thus increase detector performance.     

High-precision detection technology of NO concentration based on UV differential-adaptive interference cancellation北大核心CSCD

In order to realize high-precision monitoring of vehicle emission, a high-precision and wide-range NO measurement method was proposed. Aiming at the problem that the absorption peaks of SO2 and NO in emission overlapping in the UV band, and it was impossible to directly perform single-component gas inversion, the differential optical density (DOD) of mixed gas in the NO sensitive band (200 nm～230 nm) was first calculated by the ultraviolet differential optical absorption spectroscopy (UV-DOAS) method. Then, the adaptive interference cancellation technology was introduced to achieve rapid separation of mixed gas DOD. Finally, the least square method was used to perform the concentration inversion of separated NO. This method could achieve rapid inversion of NO concentration (volume fraction of gas) in the range of 100×10−6 to 3 000×10−6. After testing, the absolute value of the relative error of inversion is less than 10% in the concentration range of 100×10−6 to 200×10−6, and less than 5% in the concentration range of 300×10−6 to 3 000×10−6. This method has the characteristics of large measurement range and fast speed, and can meet the measurement requirements of NO concentration in the range of 3 000×10−6 in vehicle emission. © 2022 Editorial office of Journal of Applied Optics. All rights reserved.     

Convex combination of nonlinear adaptive filters for active noise control

This paper proposes a nonlinear active noise control (ANC) system based on convex combination of a functional link artificial neural network (FLANN) and a Volterra filter. Simulation study reveals enhanced noise cancelation performance of the proposed ANC system over the ones based on its component filters.