OFDM-CPM系统降低PAPR新方案研究

正交频分复用-连续相位调制(OFDM-CPM)系统通过CPM相关相位状态引入记忆,从而获得比传统调制方式更好的误码性能。降低OFDM-CPM系统中的峰值平均功率比(PAPR)是关键技术之一。利用恒包络的概念提出一种新的CE-OFDM-CPM调制方案,可以把OFDM-CPM系统的PAPR降至零分贝。     

一种低复杂度的DFT-S-OFDM系统迭代检测算法

针对LTE上行的单载波频分多址系统--离散傅立叶变换扩频的正交频分复用(DFT-S-OFDM)系统,提出了一种低复杂度的迭代检测实现方法.由于传统方法根据发射机与信道级联系统的等效传输矩阵,完成最小均方误差(MMSE)的迭代检测,但非对角矩阵求逆复杂度较高,因此,所提出的新方法对发送端DFT扩频后的信号先进行单点的MMSE检测,然后根据逆离散傅立叶变换(IDFT)解扩后的后验均值和方差等效得到输出外信息比特似然比.仿真结果表明,所提出迭代检测接收算法的性能与传统方法相近,而其实现复杂度则有较大降低.     

双正交冗余小波变换的图像去噪方法

由于正交小波变换的不具备线性相位、不具有平移不变性等特性,导致其在图像去噪领域仍存在很多问题,本文将双正交冗余离散小波变换应用到几种经典小波阈值图像去噪方法中,以克服标准正交小波变换在阈值图像去噪中存在的问题.实验证明该方法的去噪效果明显优于正交小波方法和普通双正交小波变换的去噪效果.     

Comparison between time shifted non-orthogonal frequency division multiplexing and OFDM

通过将时移参数引入多载波调制,形成了一种具有全新思想的时移非正交频分复用(TS-NFDM)调制技术,并通过理论分析和仿真实验将该技术的性能与当前在无线通信中扮演重要角色的正交频分复用(OFDM)技术进行了比较.比较结果表明,TS-NFDM技术具有明显的优势,其时移特性使其表现出许多优良的性能,其中最突出的是频带利用率高,约为OFDM的4.29倍,另外,信号功率的峰值均值比也明显低于OFDM.     

小波变换分析信号的瞬时频率分析

小波变换可以用来取代短时DFT,已经成为数字信号处理(DSP)的主流部分。在数字信号处理中,小波的尺度和频率有密切的关系。分析多个信号时不存在交差项的干扰,能够克服时频分布固有的缺点。     

离散余弦小波包变换及语音信号压缩感知

针对语音信号压缩感知问题,在研究语音离散余弦变换(Discrete Cosine Transform,DCT)系数和小波包变换(Wavelet Packet Transform,WPT)特性的基础上构造了离散余弦小波包变换(Discrete Cosine Wavelet Packet Transform,DCWPT)。DCWPT首先获取语音信号的DCT域系数,结合语音频谱特性选取部分DCT系数进行WPT变换,从而得到比DCT系数更加稀疏的DCWPT系数。为将此变换直接用于压缩感知,构造了DCWPT的正交稀疏分解矩阵并分析了其稀疏表示性能。结合稀疏表示基优化了正交匹配追踪重构算法,提出了基于DCWPT的语音信号压缩感知框架。通过压缩重构对照实验,采用主客观评价指标,得出该方法优于传统基于DCT的语音压缩感知方法的结论。     

正交小波包分析在遥感图像融合中的应用

小波变换具有优良的时频局部特性，但由于其尺度是按二进制变化的，存在“高频低分辨”这一缺陷．正交小波包分析能够将信号(图像)频带进行多层次划分，对多分辨分析没有细分的高频部分进一步分解，从而提高了频率分辨率，能有效地提取特定的频率成分．推导了小波包分析的基本原理，给出了基于正交小波包分析的遥感图像融合算法．最后，通过实例说明正交小波包分析的有效性和优越性．     

基于解析小波变换识别结构的模态阻尼参数

摘要: 在结构振动分析中,结构的模态参数尤其模态阻尼参数的准确识别是一项十分重要的任务。基于Gabor小波函数的解析小波变换(AWT)通过小波函数与复值信号的匹配机制揭示信号的幅频和相频信息以实现结构模态阻尼参数的识别。本文基于小波变换(WT)理论,讨论了Gabor小波函数的特性及解析小波变换的时频分辨率和端点效应问题;为实现结构模态阻尼参数的准确识别,我们提出了Gabor小波函数参数选取和有效信号长度确定的依据。最后,一个频率呈密集分布的三自由度(3DOF)结构的数值模拟数据验证了本文提出的模态阻尼识别方法的有效性。     

利用CPM实现自适应OFDM系统研究

在正交频分复用(OFDM)系统中应用自适应技术能有效地提高系统性能。正交频分复用-连续相位调制(OFDM-CPM)通过CPM相关相位状态引入记忆,从而获得比传统OFDM更好的误码性能。文章提出了一种利用单一的CPM调制方式实现自适应OFDM-CPM系统的新方案。仿真结果表明,选取最佳的CPM参数组合,通过改变CPM的参数来实现自适应OFDM-CPM调制,能够获得比传统调制方式要低的门限值,同时系统硬件实现更为简单。     

正交小波变换k-中心点聚类算法在故障诊断中的应用

k-中心点聚类算法(k-medoids cluster algorithm,KCA)是改进的机器学习聚类算法,该方法通过初始聚类中心选取和聚类中心更新,对无标记训练样本的学习揭示数据的内在性质及规律,从而区分出机器的运行状态。提出了一种正交小波变换k-中心点聚类算法(orthogonal wavelet transform k-medoids clustering algorithm,OWTKCA)诊断方法,利用正交小波变换(orthogonal wavelet transformation,OWT)方法提取各细节信号作为训练样本,用KCA方法进行分类。通过滚动轴承的试验数据分类结果显示,该方法相对于没有提取特征值的KCA能有效处理复杂机械振动信号,明显提高了故障数据聚类效果,缩短了聚类时间,提高了智能诊断效率。     

Algebraic wavelet filters

A method to compute the discrete wavelet transform for certain wavelet filters is proposed that takes advantage of conjugacy properties in number fields. It is shown that wavelet filters derived from compactly supported orthonormal wavelets can be approximated with arbitrary precision by the proposed wavelet filters. © 1996 John Wiley & Sons, Inc.     

基于小波系数变换的小波阈值去噪算法改进

小波阈值去噪是近年兴起的一种较好的去噪算法,其一关键点在于准确的选取阈值将细节信号和噪声信号区分开来。提出了一种算法对小波系数进行变换,将难以区分信号和噪声的区域放大,以利于阈值的选取,从而达到改进小波阈值去噪的目的。通过使用传统阈值去噪算法和该改进算法进行仿真,结果表明改进算法对去噪指标SNR、SME（平均方差）都有所改善。另外本文实验也表明改进算法可以更好的去除噪声,且较好的重现原信号的细节特征。     

Fractional wavelet transform

The wavelet transform, which has had a growing importance in signal and image processing, has been generalized by association with both the wavelet transform and the fractional Fourier transform. Possible implementations of the new transformation are in image compression, image transmission, transient signal processing, etc. Computer simulations demonstrate the abilities of the novel transform. Optical implementation of this transform is briefly discussed.     

Two-dimensional wavelet processor

An optical implementation of the two-dimensional (2-D) wavelet transform and inverse wavelet transform is performed in real time by the exploitation of a new multichannel system that processes the different daughter wavelets separately. The so-coined wavelet-processor system relies on a multichannel replication array generated that uses a Dammann grating and is able to handle every wavelet function. All channels process in parallel using a conventional 2-D correlator. Experimental results applying the Mexican-hat wavelet-decomposition technique are presented.     

Continuous two-dimensional on-axis optical wavelet transformer and wavelet processor with white-light illumination

The wavelet transform can be expressed mathematically as a convolution between the input function and a continuous set of scaled wavelet mother functions. Optics has managed to implement only the hybrid wavelet transform in which the set of scaled wavelet mother functions is discrete but the shift is continuous. White-light illumination is used to obtain a two-dimensional, fully continuous, on-axis wavelet transformer. When the illumination source is also spatially incoherent, a complete wavelet processor may be constructed.     

Optical wavelet matched filter

A shift-invariant optical continuous wavelet transform is used for pattern recognition. We propose an Voptical wavelet matched filter that performs optical wavelet transforms for edge enhancement and the correlation between two wavelet transforms in a single step. This new bandpass matched filter shows improved discrimination capability with respect to the conventional matched filter and improved signal-to-noise ratio with respect to the phase-only matched filter. The wavelet matched filter provides flexibility of an adaptive choice of the scale factors of the wavelets that permit the selection of size and orientation of the smoothing function used in edge enhancement and the optimization of the performance of the filter. Optical experimental results are shown.     

小波脊指导离散小波分层的讨论

采用小波分层方法,可以消除畸变条纹中零频对基频的影响.本文从连续小波入手,求解出二维连续小波变换的小波脊尺度因子α的公式,结合离散小波的性质,将这些α作离散化,得到其离散值2k,用数学统计的方法将离散值分组,选择出有效的统计量即包含物体信息最多的层次,对应的k值就是离散小波变换中需要的分层系数.本文方法有效地指定较好的分层层数,实现了自动化操作.     

Spatial carrier-fringe pattern analysis by means of wavelet transform: wavelet transform profilometry

We present an analysis of a spatial carrier-fringe pattern in three-dimensional (3-D) shape measurement by using the wavelet transform, a tool excelling for its multiresolution in the time- and space-frequency domains. To overcome the limitation of the Fourier transform, we introduce the Gabor wavelet to analyze the phase distributions of the spatial carrier-fringe pattern. The theory of wavelet transform profilometry, an accuracy check by means of a simulation, and an example of 3-D shape measurement are shown.     

Imaging system of wavelet optics described by the Gaussian linear frequency-modulated complex wavelet

The image formation and the point-spread function of an optical system are analyzed by use of the wavelet basis function. The image described by a wavelet is no longer an indivisible whole image. It is, rather, a complex image consisting of many wavelet subimages, which come from the changes of different parameters (scale) a and c, and parameters b and d show the positions of wavelet subimages under different scales. A Gaussian frequency-modulated complex-valued wavelet function is introduced to express the point-spread function of an optical system and used to describe the image formation. The analysis, in allusion to the situation of illumination with a monochromatic plain light wave, shows that using the theory of wavelet optics to describe the image formation of an optical system is feasible.     

Electrocardiogram de-noising based on forward wavelet transform translation invariant application in bionic wavelet domain

In this paper, we propose a new technique of Electrocardiogram (ECG) signal de-noising based on thresholding of the coefficients obtained from the application of the Forward Wavelet Transform Translation Invariant (FWT_TI) to each Bionic Wavelet coefficient. The De-noise De-noised ECG is obtained from the application of the inverse of BWT (B W T ^?1) to the de-noise de-noised bionic wavelet coefficients. For evaluating this new proposed de-noising technique, we have compared it to a thresholding technique in the FWT_TI domain. Preliminary tests of the application of the two de-noising techniques were constructed on a number of ECG signals taken from MIT-BIH database. The obtained results from Signal to Noise Ratio (SNR) and Mean Square Error (MSE) computations showed that our proposed de-noising technique outperforms the second technique. We have also compared the proposed technique to the thresholding technique in the bionic wavelet domain and this comparison was performed by SNR improvement computing. The obtained results from this evaluation showed that the proposed technique also outperforms the de-noising technique based on bionic wavelet coefficients thresholding.