有色信源卷积混合盲源分离算法

由于缺乏有色信源的时域相关性等先验信息,在设计有色信源卷积混合盲分离算法时难以利用源信号的特性,造成“有色源”的卷积混合盲分离比“白色源”的卷积混合盲分离更具挑战性。通过挖掘信源有色特性对卷积混合多项式矩阵的作用机制,提出了一种新的有色信源卷积混合盲源分离算法。首先将有色信源建模为白色信源激励有限冲击响应（Finite Impulse Response,FIR）滤波器的响应,将有色信源卷积混合模型转化为等效的白色源卷积混合模型,此时等效的卷积混合多项式矩阵即为FIR滤波器和原混合多项式矩阵的乘积;其次使用基于白化的方法获得白色激励源和等效卷积混合多项式矩阵的估计;最后利用最大公因式提取方法从等效卷积混合多项式矩阵中提取岀FIR滤波器,进而恢复出原始的有色信源。仿真结果表明,所提算法在不同信噪比下的分离性能均优于现有算法,具有良好的实用性。     

一种基于梯度信息的自适应FIR滤波器的设计

从惯性测量的应用需求出发，设计了一种基于梯度信息的自适应FIR(Finite Impulse Response)滤波器，这种自适应滤波器依照信号的梯度信息自动修正滤波器的滤波因子，从而具备自适应消噪功能。实验表明，这种滤波器较普通的FIR滤波器有更好的消噪能力。     

基于FPGA的LFM信号匹配滤波的时域实现

为解决频域法实现信号匹配滤波时硬件开销较大的问题,采用时域法实现线性调频（LFM）信号的匹配滤波。设计了一款针对LFM信号的8阶分布式结构的时域匹配滤波器;利用FPGA的ROM宏模块构建查找表,实现分布式滤波算法;基于FPGA器件完成了滤波器的设计与集成。仿真结果显示,滤波器占用170个逻辑单元、109个寄存器、3K字节存储器,逻辑资源开销较小。与传统FIR结构的乘累加算法相比,分布式滤波算法运算速度更快。     

数字FIR滤波器的设计与实现

数字滤波器是一种用来过滤时间离散信号的数字系统，通过对抽样数据进行数学处理来达到频域滤波的目的。根据其单位冲激响应函数的时域特性可分为两类：无限冲激响应（IIR）滤波器和有限冲激响应（FIR）滤波器。与IIR滤波器相比，FIR的实现是非递归的，它总是稳定的，更重要的是，FIR滤波器在满足幅频响应要求的同时，可以获得严格的线性相位特性。因此，它在高保真的信号处理，[第一段]     

基于Matlab与DSP的FIR数字滤波器软硬件实现

给出了利用Matlab与DSP技术相结合的语音信号FIR滤波的软件、硬件实现方法。分析了FIR滤波器的特性，给出了FIR滤波器的Matlab仿真，介绍了在DSP硬件系统中的实现过程，实现了对语音信号的FIR滤波处理。     

基于RLS算法的脑电信号的去噪

介绍了自适应的递归最小二乘方滤波器(RLS)和匹配滤波器,以及其去噪的处理方法。用C语言编写了递归最小二乘方滤波器,在噪声对真实信号影响不太大的情况下的通用滤波程序,并对实际提取到的EEG信号进行了RLS去噪处理和匹配滤波输出。通过Matlab 7软件绘出他的滤波输出、功率谱、匹配滤波输出图。通过观察各种输出图像,结果令人满意。     

自适应噪声抑制器的设计和Simulink验证

在测井信号的处理中,经常会遇到非平稳噪声环境下的信号检测问题,此时很难用经典的滤波器系数固定的FIR滤波器或IIR滤波器来解决噪声背景下的信号提取问题。本文首先介绍了一种系数可变的FIR滤波器实现一种不需要参考噪声的自适应噪声抑制器的基本原理,然后在此基础上阐述了在Simulink环境中建模的具体方法,最后使用该模型对一个非平稳有色噪声信号进行抑制,仿真结果表明在不需要参考噪声源时通过该自适应噪声抑制器同样可以获得比较好的噪声抑制效果。     

基于循环缓冲区FIR滤波器的设计

数字滤波技术主要包括滤波器设计及滤波过程的实现两方面内容。文中阐述了FIR滤波器基本结构,结合实例用Matlab来确定FIR滤波器系数,分析了循环缓冲区算法原理。在该算法的基础上,结合设计的滤波器实现对输入混合信号的FIR数字滤波,最后给出了滤波前后输入输出信号波形仿真。     

圆锥扫描体制雷达跟踪旋转目标的方法研究

针对圆锥扫描体制雷达对目标精密跟踪及测角时由于导弹目标自旋而引起的跟踪失控问题，提出了一种采用窄带FIR滤波器滤除自旋调制信号，提取锥扫信号的解决方法。FIR滤波器具有线性相位，但需要采用高阶滤波才能达到很好的带通特性。该方法经过计算机仿真产生高阶FIR滤波器系数，经过了仿真验证，并在导弹目标跟踪应用中取得了很好的效果。     

全相位滤波白噪声产生有色噪声及其功率谱估计

本文提出用全相位数字滤波器这种新型滤波器滤波白噪声产生有色噪声的方法,这种方法比用传统FIR滤波器产生的有色噪声频谱泄漏少,阻带衰减功率大等优点.并且分别用Welch法和全相位法对在有色噪声中混入的双频小信号余弦波进行谱估计,实验证明全相位谱估计性能优于经典谱估计.     

A higher-order statistics-based adaptive algorithm for lineenhancement

A novel higher order statistics (HOS) based adaptive filtering algorithm for line enhancement is suggested. The enhancement process is achieved by filtering the noisy signal through an adaptive FIR filter. The steady state of the impulse response of this filter is proportional to a selected one-dimensional (1-D) slice of the fourth-order mixed cumulant of the input signal. It is shown that this slice is comprised of noiseless sinusoids if the input signal is comprised of sinusoids embedded in Gaussian noise. Therefore, the algorithm is considered to be a suitable one in processing sinusoids embedded in highly colored Gaussian noise. Simulation results verify the performance of the proposed algorithm     

Least squares acceleration filtering for the estimation of signalderivatives and sharpness at extrema [and application to biologicalsignals]

A family of finite impulse-response (FIR) filters is derived which estimate the second derivative or "acceleration" of a digitized signal. The acceleration is obtained from parabolas that are continuously fit to the signal using a least squares optimization criterion. A closed-form solution for the filter coefficients is obtained. The general approach is computationally simple, can be performed in real-time, and is robust in the presence of noise. An important application of the method, that of measuring sharpness in biologic signals, is presented using the electroencephalogram (EEG) and electrocardiogram (EKG) signals as examples. Furthermore, the design method is extended to derive FIR filters for estimating derivatives of arbitrary order in digital signals of biologic or other origins.     

基于RLS算法实现激光陀螺抖动信号剥除

为了减小陀螺输出数据的时延,以满足机械抖动激光陀螺在快速跟踪中的应用,基于递归最小二乘(RLS)自适应滤波技术实现了激光陀螺抖动信号的剥除。首先对RLS自适应对消去抖算法进行了理论分析,其次通过通用串行总线接口将A/D采集的抖动反馈信号和激光陀螺计数脉冲信号传至上位机,最后基于MATLAB编写了RLS自适应程序,实现了激光陀螺抖动信号的剥除。剥除后的陀螺信号再经过11阶的有限脉冲响应滤波器和陀螺输出直接经过31阶的滤波器剩余的脉冲数基本相当,而时间延迟却明显减小。结果表明,该算法具有较快的收敛速度且能够有效去除激光陀螺计数脉冲中的抖动成分。     

位置敏感探测器的信号噪声自适应抑制方法

针对位置敏感探测器噪声来源及特点,提出了一种基于自适应FIR维纳滤波器的自适应抑制方法。该方法以维纳滤波器为数字滤波器,自适应地调整传输特性,提高PSD的信噪比,从而大幅提高了PSD应用系统的测量精度。     

Adaptive filter for event-related bioelectric signals using animpulse correlated reference input: comparison with signal averagingtechniques

Many bioelectric signals result from the electrical response of physiological systems to an impulse that can be internal (ECG signals) or external (evoked potentials). In this paper an adaptive impulse correlated filter (AICF) for event-related signals that are time-locked to a stimulus is presented. This filter estimates the deterministic component of the signal and removes the noise uncorrelated with the stimulus, even if this noise is colored, as in the case of evoked potentials. The filter needs two inputs: the signal (primary input) and an impulse correlated with the deterministic component (reference input). We use the LMS algorithm to adjust the weights in the adaptive process. First, we show that the AICF is equivalent to exponentially weighted averaging (EWA) when using the LMS algorithm. A quantitative analysis of the signal-to-noise ratio improvement, convergence, and misadjustment error is presented. A comparison of the AICF with ensemble averaging (EA) and moving window averaging (MWA) techniques is also presented. The adaptive filter is applied to real high-resolution ECG signals and time-varying somatosensory evoked potentials.     

Redundant Paraunitary FIR Transceivers for Single-Carrier Transmission Over Frequency Selective Channels With Colored Noise

Recently, the use of redundant memoryless single-carrier transmitters has been reported as an efficient choice to reduce distortions introduced by finite-impulse response (FIR) channels. In this work, redundant FIR transceivers are proposed to address not only channel frequency selectivity but additive colored noise, which strongly degrades the performance of memoryless transceivers. The transmitter is shown to be paraunitary, resulting in a simple receiver. The proposed system is optimized like a modulated filter bank. Channel shortening and post-combiner equalizers are used to improve system performance. Comparisons with recent proposed schemes are presented, illustrating the efficiency of the new structure for selective channels with colored noise.     

基于DSP5509A的自适应系统识别的实现

在数字信号处理中,自适应系统识别是处理一些未知系统的重要方法。文中在论述自适应滤波器的基本原理和LMS算法的基础上,阐述了自适应系统识别的实现原理。然后在DSP的集成开发环境下设计一个随机白噪声信号发生器,用来产生自适应滤波器和未知系统所需的测试数据。最后采用FIR滤波器作为待识别的未知系统,并利用TI公司的DSP TMS320VC5509A芯片实现了自适应系统识别。实验结果表明,该方法实现比较简单,且能达到信号处理的高精度和高效性。