基于小波变换的音频信号去噪

本文主要介绍基于小波变换的软阈值和硬阈值在数据处理中的应用，并用Matlab软件进行仿真。     

生产过程中的小波阈值信号去噪方法

在工业生产过程中,由于设备所收集到的混合信号中包含大量的背景噪声信号,而这些背景噪声信号会影响到异响有用信号的提取。因此,为对收集的信号进行消噪,提出了小波阈值去噪中估计小波系数的软阈值和硬阈值方法,结合硬阈值和软阈值方法各自的特点,采用了几种改进的方案,分别是多项式插值法,软、硬阈值折衷法和模平方处理方法。最后给出了数值试验,结果说明,改进的小波阈值方法都得到了较好的去噪效果,为工业生产过程优化信号提取提供了依据。     

一种基于小波阈值去噪的改进方法

小波理论是一新兴的信号处理理论。它在时间和频率上都有很好的局部性：分析低频信号时，其时间窗很大；分析高频信号时，其时间窗较小。小波理论已成为信号去噪处理中的一种重要的工具。基于传统的阈值去噪方法，在分析研究了它们的优缺点之后．本着改进滤波效果，提高去噪质量的目的，提出了一种改进方法。该改进方法克服了传统阈值去噪方法的缺陷。并适用于进一步的自适应滤渡的需求．仿真实验证实了该改进方法的有效性和优越性。     

健康预测中信号去噪算法的研究

在D.L.Dobono和I.M.Jobnstone提出的多分辨分析小波阈值去噪算法的基础上,提出了一种新的阈值函数.与传统的硬阈值和软阈值比,此函数不仅易于计算,而且具有优越的数学特性和清晰的物理意义.经对桥梁检测数据进行去噪试验,结果表明,该方法可以有效地去除白噪声干扰,无论在视觉效果上还是在信噪比和均方误差定量指标上均明显优于常用的软、硬阈值及改进的软硬阈值折中算法,充分体现出小波阈值去噪方法的优越性.     

基于小波阈值改进算法的动调陀螺信号去噪

针对传统阈值函数对动调陀螺输出信号去除噪声存在阈值函数不连续或恒定偏差问题,在D.L.Donoho和I.M.John-stone提出的多分辨分析小波阈值去噪方法的基础上,提出了一种新的阈值函数;新阈值函数表达式简单易于计算,在对动调陀螺漂移信号去除噪声时,它既克服了硬阈值函数不连续的缺点,同时又克服了软阈值函数中估计小波系数与分解小波系数之间存在着恒定偏差的缺陷,具有硬、软阈值函数不可比拟的灵活性;通过动调陀螺实测信号的实验表明,新阈值函数可以有效地去除白噪声干扰,无论在视觉效果上还是在信噪比和均方误差定量指标上,均优于传统的去噪方法,具有较高的实用价值。     

一种基于小波阈值去噪的改进方法

小波理论是一新兴的信号处理理论,它在时间和频率上都有很好的局部性:分析低频信号时,其时间窗很大;分析高频信号时,其时间窗较小。小波理论已成为信号去噪处理中的一种重要的工具。基于传统的阈值去噪方法,在分析研究了它们的优缺点之后,本着改进滤波效果,提高去噪质量的目的,提出了一种改进方法。该改进方法克服了传统阈值去噪方法的缺陷,并适用于进一步的自适应滤波的需求,仿真实验证实了该改进方法的有效性和优越性。     

基于小波变换的图像阈值去噪的改进方法

基于Donoho提出的传统的阈值去噪方法,提出了一种新的阈值函数,并应用于图像的去噪.与Donoho的软阈值和硬阈值函数相比,这种新的阈值函数有更多的优点:可以实现能量自适应去噪;能够保存图像的边缘信息;函数的表达式简单,避免了硬阈值函数的不连续性;相比软阈值和硬阈值函数,新阈值函数更灵活.仿真结果表明,改进后的方法应用于图像去噪,无论是视觉效果还是信噪比都有了改善.     

低复杂度的空间调制信号检测

空间调制(SM)算法在接收端常用最大释然(ML)信号检测获得发送天线编号以及调制符号,恢复发射信息比特,但是ML算法复杂度随着天线数和调制阶数的增加呈指数增长,不具有实用性。针对该难题,提出一种新的低复杂度次最优检测算法。通过设置合理的判决门限将信号矢量检测(SVD)和硬限最大似然(HL-ML)算法进行联合。蒙特卡洛仿真结果表明,该算法的误比特率检测性能比SVD算法更接近ML算法,且复杂度与ML算法相比降低了85%。     

信号相位匹配噪声估计的小波去噪方法

多数小波阈值去噪方法需要根据噪声方差来计算相应的阈值,所以噪声方差的估计将直接影响阈值去噪的效果.提出了一种新的相位匹配的噪声方差估计方法,利用该方法实时地逼近当前噪声,建立新的噪声的阈值求取方法.通过实验证明该方法能够大幅度提高信噪比,可以取得非常好的去噪效果.     

带噪语音信号小波去噪算法研究

去噪问题是信号处理中必不可少的问题。滤波作为传统的去噪方法,主要包括线性滤波和非线性滤波。噪声与信号频率重叠,传统方法要想取得良好的去噪效果必须牺牲部分信号。现有的小波模极大值去噪方法虽然有较好的去噪效果,但是该方法计算量大。小波阈值去噪方法更简单,但小波重构后的小波系数与噪声的小波系数存在恒定的偏差。在阈值去噪方法的基础上提出一种改进算法,仿真结果表明该算法在加性高斯白噪声污染下表现出较好去噪效果。     

红外低硫传感器信噪比改善方法研究

低硫的红外探测是一个非常重要的研究领域,但由于红外硫的吸收峰在一个特殊的波段,与人体红外波段重合,所以国外的先进技术大都对中国封锁,而国内的低硫传感器存在交叉吸收误差,检出限不够、检测精度低等缺陷;文章以煤中硫元素的测试为基础,研究采用了电调制热释电红外传感器在测量硫元素过程中存在的以上问题,主要开展了探测器稳定性、恒温测试、气室噪声、滤波等改善传感器信噪比的相关改进设计和实验,并提出了优化的方案,优化后经过实验测试,整个测试系统的信噪比提升近50%,检出限从原来的100 ppm提升到近10 ppm;低硫测量平均值为0.382%,SD为0.006%,RSD为1.2%,瓶内RSD为0.9%;达到了低硫的高精密测试。     

Design optimization using signal-to-noise ratio

This paper shows how design optimization can be achieved using signal-to-noise (S/N) ratios. A case of maintenance float policy is used to illustrate the application presented here. Basically, this involves the implementation of a robust design plan in simulation analysis. The design plan is based on the use of orthogonal arrays introduced by Taguchi. Through the application of Taguchi's S/N ratio, we demonstrate that the best design plan from an experimental design can be determined. This has several implications: (1) It reduces the experimentation time, (2) it can identify a fractional design that contains the best design plan and that design plan could be studied for full experimentation, (3) within a subset of a fractional design plan, the best design point can be found, and (4) the cost of experimentation is significantly reduced since minimal number of runs is required to identify the best design point. Finally, this important result helps experimenters to select a fractional design plan that contains the “best design point”.     

地震信号小波变换的去噪方法

运用模极大值法基本原理进行地震信号去噪研究,进而运用二次小波变换原理通过低层系数处理对常用小波去噪方法进行改进.通过合成不同的染噪地震信号,由一系列仿真实验对模拟地震信号进行不同尺度的小波分解与重构,从而实现最优小波分解尺度上的地震信号噪声去除.与常用的快速傅立叶转换方法比较,仿真结果表明,该小波变换方法能够有效去除地震勘探信号中的噪声,并且针对系数的二次小波变换可以明显改进去噪的效果.     

低信噪比下基于功率谱熵的语音端点检测算法

为了解决短波通信中语音检测的问题,针对短波语音信噪比低,噪声复杂的特点,对幅度谱熵算法进行了修正,选取功率谱熵作为VAD特征,加入谱熵平滑和hangover设计,研究了基于功率谱熵的语音端点检测算法。实验证明,算法对几种典型的短波语音均有比较理想的性能。     

Interpreting image-based methods for estimating the signal-to-noise ratio

The signal-to-noise ratio (SNR) of remotely sensed imagery has been estimated directly using a variety of image-based methods such as the Homogeneous Area (HA) and Geostatistical (GS) methods. However, previous research has shown that such estimates may be dependent on land cover type. We examine this dependence on land cover type using Compact Airborne Spectrographic Imager (CASI) imagery of an agricultural region in Falmouth, Cornwall. The SNR was estimated using the GS method for six different land covers and a range of wavelengths. Large differences in the SNR existed between land cover types. It follows that single estimates of SNR (e.g. for one land cover) should not be associated with an image (as a whole). It is recommended that either (i) each statistic is reported per land cover type per wavelength or (ii) that an image of local statistics is reported per wavelength. The regression of noise on signal can be used to separate independent noise (intercept) from signal-dependent noise (slope). Variation in the noise and SNR estimates can be used to (i) allow more accurate prediction of the SNR and (ii) provide information on uncertainty.     

化学离子迁移谱检测仪信号降噪方法研究

化学离子迁移谱检测仪是对化学毒剂、有毒有害气体等化学物质进行痕量检测和分析的一种有效的快速现场检测仪器。介绍了其组成结构和工作原理及其信号的产生,针对该检测仪中的信号经常存在的噪声污染问题,分析了IMS信号的特性,介绍了几种降噪方法的基本原理及其在信号降噪中的应用,通过计算机仿真对实际采集的IMS信号进行了降噪处理。仿真结果表明,这些降噪方法都能在一定程度上对IMS信号进行了降噪,相对来说,小波分析方法是一种更为有效的降噪方法,这为实现对IMS信号的快速有效识别奠定了基础。     

Controllable single accumulated state-sequential acquisition with low signal noise ratio

The sequential estimation (SE) algorithm has a poor performance in the environment with a low signalto-noise ratio (SNR) and a high bit error rate (BER), especially for unknown initial acquisition sequence. This paper summarizes the conventional sequence acquisition model, and discovers its several problems, which are caused by accumulating sequence innovation to all of the received sequences dispersedly. To solve these problems, the paper presents a new algorithm, CSAS-SA (controllable single accumulated state-sequential acquisition). This algorithm accumulates the sequence innovation to a single appointed sequence state and makes the useful information accumulated effectively. Through simulation, CSAS-SA has a higher probability of success acquisition. When SNR equals −3 dB, the performance can be improved by 70%. Supported by the Program for New Centery Excellent Talents in University and the National High-Tech Research and Development Program of China (Grant No. 2007AA01Z434)     

Localization of furniture parts by integrating range and intensity data robust against depths with low signal-to-noise ratio

In this article we present an approach for localizing planar parts of furniture in depth data from range cameras. It estimates both their six-degree-of-freedom poses and their dimensions. The system has been designed for enabling robots to autonomously manipulate furniture. Range cameras are a promising sensor category for this application. As many of them provide data with considerable noise and distortions, detecting objects, for example, using canonical methods for range data segmentation or feature extraction, is complicated. In contrast, our approach is able to overcome these issues. This is done by combining concepts of 2D and 3D computer vision as well as integrating intensity and range information in multiple steps of our processing chain. Therefore it can be employed on range sensors with both low and high signal-to-noise ratios and in particular on time-of-flight cameras. This concept can be adapted to various object shapes. It has been implemented for object parts with shapes similar to ellipses as a proof-of-concept. For this, a state-of-the-art ellipse detection method has been enhanced regarding our application.     

Bioacoustic signal denoising: a review

Artificial Intelligence Review - Animal biodiversity has been experiencing rapid decline due to various reasons such as habitat loss and degradation, invasive species, and environment pollution....