简述信号特征提取使用小波变换的优点

通过对小波变换所进行的理论分析和计算机模拟发现,利用小波变换具有的高低频分离的特点,可在不丢失原信号重要信息成分的前提下,将原光谱信号的边缘部分进行滤化处理,消除了噪音信息,重构出更加清晰的光谱特征图形,从而提高了信号的清晰度,为信号的预处理提供了更加方便的条件。该信号特征提取的方法,与傅氏变换相比较,具有多项明显的优点,在实际工程应用中具有重要的意义。     

基于小波变换的信号去噪研究

小波变换在信号去噪的应用中有很大的优势,它弥补了傅里叶变换在信号去噪中的局限。小波变换在时间域和频率域都具有良好的局部特性,可以聚焦到信号的任意细节。根据信号的特性利用小波变换的处理方法能够有效的将有用信号与噪声分离开来从而达到去噪的效果。     

织机声信号瞬态特征分析方法

提出了一种采用Ｍｏｒｌｅｔ小波变换实现织机声信号分析的方法,并藉助高速信号处理器和微机系统予以实现。对典型织机声信号进行了小波变换分析,获得了典型织机声信号的三维小波变换谱。实验结果表明,该方法是有效的。同短时傅里叶变换分析法相比较,织机声信号的小波变换分析法具有较好的分析性能。     

M带小波分析综述

小波分析是在傅立叶变换的基础上发展起来的一种时频分析方法.作为一种新的变换域信号处理方法,小波变换尤其擅长处理在非平稳信号的分析.本文主要根据小波变换的特点,介绍了连续小波交换,M带离散小波变换的分解与重构算法并简单介绍了M带小波在信号处理中的应用.     

盲分离技术在语音信号处理中的研究与应用

盲分离技术是信号处理领域研究的热点问题,在源信号和混合过程未知的情况下,从混合信号中分离出源信号.重点研究了混合语音信号的盲分离方法,对语音信号进行加窗傅立叶变换,采用定点ICA算法对混合语音信号进行分离.最后使用Matlab软件对算法进行了仿真.     

基于约束模糊聚类的抗电力雷电波干扰信号检测

提出了一种基于约束模糊聚类的抗电力雷电波干扰信号检测方法。利用信号采集设备采集信号,并对信号进行傅里叶变换处理,为信号检测提供准确的数据基础。利用约束模糊聚类方法,对抗电力雷电波干扰信号进行检测。实验结果表明,这种算法能够有效提高检测的准确性,取得了令人满意的效果。     

小波变换在雷达信号处理中的应用

由于雷达系统的复杂性、杂波回波信号中的噪声以及系统和硬件内部的干扰,研究雷达回波抑制技术就显得尤为重要。文章对回波信号的去噪方法进行了小波变换分析。研究表明,采用小波变换的雷达回波信号处理方法,能够有效抑制噪声、消除干扰,实现回波信号的去噪处理。     

小波变换在信号奇异性检测中的应用

小波变换突破了传统傅里叶变换等信号处理方法的限制,在时域和频域上可同时对信号实现局部化处理,这更符合信号非平稳的变频带结构特征,因而在信号检测奇异性等方面具有广泛的应用价值。本文简要地介绍了小波应用在信号奇异性检测方面变换的基本原理,并通过仿真实验进行了验证。     

钻井模拟中测井信号小波去噪的最优阈值选取方法

钻井模拟中的测井信号往往存在着与地层无关的噪声干扰,必须进行去噪处理。小波变换可以滤除测井信号的噪声和干扰,但其去噪效果与阈值的选取有关。本文从理论上介绍了阈值的选取准则及阈值选取方法,再从实验角度对四种阈值选取方法（Stein无偏似然估计阈值法、固定阈值法、混合型阈值法和最小最大准则阈值法）进行了分析计算,最终选定混合型阈值小波消噪法去除测井信号的噪声。对实际测井信号的处理效果表明,混合型阈值小波消噪法不仅去噪效果好,而且较好的保留了测井信号的分辨率,适用于测井信号的去噪。     

基于自然对数似然分解的频域展宽信号能量聚集

主动声呐自导系统发出的回波信号表现为一种频域展宽信号,对频域展宽信号的准确检测是实现声呐精确探测的技术难题。传统方法中采用分数阶傅立叶变换方法设计检测算法,声呐自导系统径向运动过程中的回波与样本之间的失配导致检测性能下降。利用自然对数变换对线性调频信号的能量聚焦特性,提出一种基于自然对数似然分解的频域展宽信号能量聚集方法,构建主动自导系统回波频域展宽信号模型构建,进行算法改进设计,实现对主动声呐自导系统回波信号的准确检测。仿真实验结果表明,算法能使回波信号在自然对数频域产生明显的能量聚集,提高检测性能,检测概率较传统方法提高明显。     

经验模式分解去斑和顶帽变换在舰船检测预处理中的应用

提出了一种基于经验模式分解去斑和顶帽变换背景不均匀的预处理方法. 经验模式分解去斑算法先对图像每一列进行经验模式分解得到IMF函数,然后将原信号与第一、二模态相减得到初步处理图像,再对该图像每一行重复该操作从而得到去斑图像,该算法有效地去除斑点噪声;顶帽变换则有效地补偿了海浪带来的局部不均匀的背景亮度,提高了图像的信杂比,有利于目标的检测. 仿真结果证明了算法的有效性.     

调和NA群上几种新的Hardy不确定原理

介绍了调和NA群上的Radon变换,以及这个变换和Helgason-Fourier变换之间的关系。基于这些变换,将实直线R上Morgan形式的Hardy不确定原理和Cowling-Price形式的Hardy不确定原理推广到调和NA群。     

Identification of a class of signals imbedded in high measurement noise

The Kalman filtering algorithm is used to identify a class of signals imbedded in high amplitude measurement noise. The considered class of signals is first modeled empirically as a nonlinear equation. The equation is then linearized and formulated as a Kalman filtering state estimation problem. Computer simulations yield excellent results for a variety of examples, a couple of which are presented in this paper.     

Application of a transversal laguerre network in adaptive equalization

Synchronous data transmission systems that transmit information over dispersive channels often employ adaptive equalization techniques in the processing of the received signals. Most equalizers presently used in communication systems are of the tapped delay line (TDL) type. In this paper, we propose a class of adaptive equalizers of which the TDL equalizer is a member. Another interesting member of this class is the Laguerre adaptive equalizer which is to be introduced in this paper. The configuration of the Laguerre equalizer is developed. It is found, as shown by the examples, that the Laguerre equalizer is more accurate, and is less sensitive to timing error than the conventional TDL equalizer.     

雷达信号的时——频分析和应用

针对常见的雷达脉冲信号（常规信号（NS）,线性调频信号（LFM）,双线性调频信号（DLFM）运用时频工具对调制方式的识别进行研究。运用两种时频分析方法1.短时傅里叶变换2.相位展开算法.通过这两种算法对雷达信号的调制方式进行分析,并通过仿真得到雷达信号的时--频分布以及时—频,时—相曲线,对仿真结果进行研究。通过仿真实验表明,雷达信号调制方式识别算法是可行的,有效的,而且具有良好的性能。     

Stability and L2-gain analysis for switched neutral systems with mixed time-varying delays

This paper considers the stability and L₂-gain for a class of switched neutral systems with time-varying discrete and neutral delays. Some new delay-dependent sufficient conditions for exponential stability and weighted L₂-gain are developed for a class of switching signals with average dwell time. These conditions are formulated in terms of linear matrix inequalities (LMIs) and are derived by employing free weighting matrices method. As a special case of such switching signals, we can obtain exponential stability and normal L₂-gain under arbitrary switching signals. Finally, two numerical examples are given to illustrate the effectiveness of the theoretical results.     

Approximation based on orthogonal and almost orthogonal functions

In this paper, we define a class of almost orthogonal rational functions of Legendre type in a new manner. Relations of these functions with classical exponentional functions orthogonal over interval (0, ∞), as well as classical polynomials orthogonal over (0, 1) are explained. Defining relations of these functions can be used for designing almost orthogonal filters. These filters are generators of orthogonal signals and can be successfully applied in finding the best signal approximation in the sense of the mean square error. The filters orthogonal property enables building of physical (in this case electrical) models of dynamical systems (the sources of signals to be approximated) either with less components for the same model accuracy or higher accuracy for the same number of components than the other known models. New filters represent further improvement of previously designed filters, by the same authors, in the sense of simplicity, higher accuracy, lesser approximation time and even a possibility to approximate signals generated by systems with built-in imperfections. Series of experiments were performed to analyze the dependence of approximation accuracy and the number of filters sections.     

A fractional Gabor expansion

We present a fractional Gabor expansion on a non-rectangular time-frequency lattice. Sinusoidal analysis used in the traditional Gabor expansion is not appropriate for a compact representation for chirp-type signals. Basis functions of the proposed expansion are obtained via fractional Fourier basis. Completeness and biorthogonality conditions of the new expansion are derived.     

具有确定逼近域的自适应模糊DSC控制

针对一类不确定非线性时滞系统,提出了一种具有确定逼近域的自适应模糊控制器的设计方案。在动态面控制（DSC）的基础上,通过时滞代换技巧,使得自适应模糊逼近器的输入为参考信号,从而可以明确定义逼近域,同时可以处理系统中完全未知的时滞信号。基于Lyapunov-Krasovskii范函,证明闭环系统所有信号为半全局一致有界的,并且跟踪误差可以收敛到原点附件的一个小邻域内。仿真结果进一步说明了该方法的有效性。