Complexity-constrained best-basis wavelet packet algorithm forimage compression

The concept of adapted waveform analysis using a best-basis selection out of a predefined library of wavelet packet (WP) bases allows an efficient image representation for the purpose of compression. Image coding methods based on the best-basis WP representation have shown significant coding gains for some image classes compared with methods using a fixed dyadic structured wavelet basis, at the expense however, of considerably higher computational complexity. A modification of the best-basis method, the so-called complexity constrained best-basis algorithm (CCBB), is proposed which parameterises the complexity gap between the fast (standard) wavelet transform and the best wavelet packet basis of a maximal WP library. This new approach allows a `suboptimal' best basis to be found with respect to a given budget of computational complexity or, in other words, it offers an instrument to control the trade-off between compression speed and, coding efficiency. Experimental results are presented for image coding applications showing a highly nonlinear relationship between the rate-distortion performance and the computational complexity in such a way that a relatively small increase in complexity with respect to the standard wavelet basis results in a relatively high rate distortion gain     

Optimal bit allocation and best-basis selection for wavelet packetsand TSVQ

To use wavelet packets for lossy data compression, the following issues must be addressed: quantization of the wavelet subbands, allocation of bits to each subband, and best-basis selection. We present an algorithm for wavelet packets that systematically identifies all bit allocations/best-basis selections on the lower convex hull of the rate-distortion curve. We demonstrate the algorithm on tree-structured vector quantizers used to code image subbands from the wavelet packet decomposition.     

微弱动不平衡信号的谐波小波包提取

在刚性转子动平衡修正中,对有效的振动信号进行检测和提取是直接关系到后期计算与动平衡修正效果好坏的最关键的一个环节,谐波小波具有良好的盒形谱特性、存在明确的函数表达式、时域定位准确和算法实现简单等优点,而在谐波小波的基础上实现的谐波小波包算法既拥有谐波小波的优点,并且还能对分析频段进行任意的划分,以便提取和分析更加细致的信息,通过模拟给出了采样信号,并使用谐波小波包算法对采样信号进行滤波处理,有效地滤除了干扰信号,最终成功地提取到了目标振动信号。     

Adaptive wavelet packet basis selection for zerotree image coding

Image coding methods based on adaptive wavelet transforms and those employing zerotree quantization have been shown to be successful. We present a general zerotree structure for an arbitrary wavelet packet geometry in an image coding framework. A fast basis selection algorithm is developed; it uses a Markov chain based cost estimate of encoding the image using this structure. As a result, our adaptive wavelet zerotree image coder has a relatively low computational complexity, performs comparably to state-of-the-art image coders, and is capable of progressively encoding images.     

基于最优小波包基的电能质量扰动数据的压缩

针对电能质量扰动信号的频率变化十分广泛（最高达到MHz）的特点，在小波压缩的基础上，提出将基于最佳小波包基的数据分析方法应用于电能质量数据压缩，利用最佳小波包基的快速搜寻算法对高，低频分量同时进行分解，再对扰动数据进行压缩重构，并将其与基于小波变换的数据压缩方法进行仿真比较。结果表示，对于暂态信号，在压缩比大致相同的情况下，基于最佳小波包基的数据压缩效果比基于传统小波的数据压缩效果好，而对于稳态信号，基于两种方法的压缩效果相当．     

Fuzzy wavelet packet based feature extraction method and its application to biomedical signal classification

In this paper, we develop an efficient fuzzy wavelet packet (WP) based feature extraction method for the classification of high-dimensional biomedical data such as magnetic resonance spectra. The key design phases involve: 1) a WP transformation mapping the original signals to many WP feature spaces and finding optimal WP decomposition for signal classification; 2) feature extraction based on the optimal WP decomposition; and 3) signal classification realized by a linear classifier. In contrast to the standard method of feature extraction used in WPs, guided by the criteria of signal compression or signal energy, our method is used to extract discriminatory features from the WP coefficients of the optimal decomposition. The extraction algorithm constructs fuzzy sets of features (via fuzzy clustering) to assess their discriminatory effectiveness. This paper includes a number of numerical experiments using magnetic resonance spectra. Classification results are compared with those obtained from common feature extraction methods in the WP domain.     

基于小波包变换和特征选择的雷达辐射源信号识别

为了提高雷达辐射源信号的正确识别率以满足现代电子对抗的需要，提出一种基于小波包变换和特征选择的雷达辐射源信号识别新方法。先采用小波包变换进行特征提取，再采用基于量子遗化算法的相像系数特征选择法来挑选出小波包特征中分辨能力强的特征。仿真实验结果显示，该方法用较少的特征能获得较高的正确识别率，具有一定的参考价值。     

Wavelet and wavelet packet compression of electrocardiograms

Wavelets and wavelet packets have recently emerged as powerful tools for signal compression. Wavelet and wavelet packet-based compression algorithms based on embedded zerotree wavelet (EZW) coding are developed for electrocardiogram (ECG) signals, and eight different wavelets are evaluated for their ability to compress Holter ECG data. Pilot data from a blind evaluation of compressed ECG's by cardiologists suggest that the clinically useful information present in original ECG signals is preserved by 8:1 compression, and in most cases 16:1 compressed ECG's are clinically useful     

Wavelet and wavelet packet compression of phonocardiograms

The first reported method intended for the compression of the phonocardiogram, using wavelet coefficients thresholding, together with Huffman and run length encoding coding techniques to obtain further compression is described. Results show better compression rates and lower distortion than standard audio compression techniques.     

Hierarchical quantization indexing for wavelet and wavelet packet image coding

In this paper, we introduce the quantization index hierarchy, which is used for efficient coding of quantized wavelet and wavelet packet coefficients. A hierarchical classification map is defined in each wavelet subband, which describes the quantized data through a series of index classes. Going from bottom to the top of the tree, neighboring coefficients are combined to form classes that represent some statistics of the quantization indices of these coefficients. Higher levels of the tree are constructed iteratively by repeating this class assignment to partition the coefficients into larger subsets. The class assignments are optimized using a rate-distortion cost analysis. The optimized tree is coded hierarchically from top to bottom by coding the class membership information at each level of the tree. Context-adaptive arithmetic coding is used to improve coding efficiency. The developed algorithm produces PSNR results that are better than the state-of-art wavelet-based and wavelet packet-based coders in literature.     

Wavelet packet division multiplexing and wavelet packet designunder timing error effects

Wavelet packet division multiplexing (WPDM) is a multiple signal transmission technique in which the message signals are waveform coded onto wavelet packet basis functions for transmission. The overlapping nature of such waveforms in time and frequency provides a capacity improvement over the commonly used frequency division multiplexing (FDM) and time division multiplexing (TDM) schemes while their orthogonality properties ensure that the overlapping message signals can be separated by a simple correlator receiver. The interference caused by timing offset in transmission is examined. A design procedure that exploits the inherent degrees of freedom in the WPDM structure to mitigate the effects of timing error is introduced, and a waveform that minimizes the energy of the timing error interference is designed. An expression for the probability of error due to the presence of Gaussian noise and timing error for the transmission of binary data is derived. The performance advantages of the designed waveform over standard wavelet packet basis functions are demonstrated by both analytical and simulation methods. The capacity improvement of WPDM, its simple implementation, and the possibility of having optimum waveform designs indicate that WPDM holds considerable promise as a multiple signal transmission technique     

分组交换网络传输信道分类选择算法优化研究

为了提高分组交换网络的信道均衡性,改善通信质量,降低网络传输的误码率,提出一种基于判决反馈自适应筛选的分组交换网络传输信道分类选择算法。采用自适应加权控制对分组交换网络的信道相位信息进行星座图划分,采用横向时域滤波器方法进行信道中的干扰抑制,然后结合判决反馈自适应筛选方法实现网络传输信道的分类选择及均衡处理。最后进行实验分析,结果表明采用该算法进行分组交换网络传输信道分类选择时,信道的自适应均衡性能较好,网络数据传输的误码率较低。     

Properties determining choice of mother wavelet

Properties of wavelets with finite as well as infinite support are summarised to facilitate mother wavelet selection in a chosen application. The quantitative guidelines reduce dependence on trial-and-error schemes resorted to for selection and underscore the importance of such selection in any application of interest. In wavelet-based image sequence superresolution, studied during the last four years, the use of a B-spline mother wavelet is justified.     

蓝牙分组传输性能分析与自适应分组选择策略

分析了蓝牙2．0＋EDR新规范定义的3种调制方式在AWGN信道下的位错误率与平均接收信噪比的关系，推导了ACL分组的重传概率与平均接收信噪比的函数表达式。通过分组的重传概率与特性分析了ACL分组的传输性能，包括平均吞吐量、平均重传次数、平均传输时延等。提出了AWGN信道下的自适应分组选择策略，通过在不同的信噪比情况下选择合适的分组类型进行传输而获得最大吞吐量，给出了进行分组类型切换的信噪比门限值。分析结果与提出的策略适用于蓝牙数据传输性能的优化。     

小波包分解对心理声学模型的改进

为了改变常用心理声学模型中均匀谱分析造成的时频分辨率不足的问题,采用小波包分解对信号进行分析.通过Matlab对信号进行小波包分解处理,代替常用心理声学模型的FFT,改善了时频分辨率不足的问题,且通过小波包分解得到的频带划分.比常用心理声学模型得到的频带划分更接近于人耳的临界频带,更适应于人耳的听觉特性.     

Matched wavelet filtering of signals with change scale

A new matched filtering method with the use of normalization “in terms of level”, when the scale of signals is different, is suggested.     

基于小波和小波包变换的医学图像融合比较

分别用小波变换和小波包变换对CT和PET图像进行融合,用常用的十种图像融合质量评价指标对融合效果进行比较.结果表明小波包变换的融合质量评价指标只有部分是优于小波变换的.在对CT和PET图像进行融合时,小波包并不一定更占优势,要根据自己的实际需求来决定选择使用小波变换还是小波包变换.     

小波包和高阶统计量相结合的红外弱小目标检测

针对单帧红外图像中的弱小目标检测问题,提出了一种结合小波包和高阶统计量的新方法。首先,利用小波包变换对图像进行频域上的分解。然后,针对小波包树上的节点,由低到高采用基于四阶累计量的高斯判别准则合并相邻四个全高斯性小波包系数,得到图像的最优划分。接下来,将最低频带上的小波包系数和高斯性小波包系数置零来分别抑制背景杂波和噪声。最后,采用这些新的系数即可重建检测结果。实验结果表明:该方法能够稳健、有效地检测红外弱小目标。     

基于小波包去噪和EMD的混合算法

经验模态分解(EMD)是希尔伯特?黄变换(HHT)中的关键步骤,并伴有过冲和端点效应的产生.利用遗传算法(GA)对支持向量机(SVM)中的未知参数:惩罚函数 C和高斯核函数中的预设参数σ进行优化选取,运用 GA-SVM 对信号进行端点延拓来处理端点效应问题并提出采用分段三次 Hermite多项式插值进行包络线拟合;为了机械设备早期故障频率的特征提取,采用小波包降噪预处理,结合改进的 Hilbert?Huang变换进行轴承故障特征频率的提取实验;实验表明该方法提高了故障频率提取的准确性.     

谐波小波在TDLAS 信号分析中的应用

波长调制谱技术（WMS）在慢扫描信号基础上叠加上高频的调制电流,并加到半导体激光器的驱动电流上,于是激光频率在线性扫描的同时受交流调制。频率调制的激光束在通过吸收气体以后,其吸收线的强度也受到相同频率调制。采用谐波小波方法作为数据解调的手段,对WMS技术产生的信号进行处理并实现了2f信号的提取。采用这种方法对波数为7185.6 cm-1的水蒸气谱线进行测量实验,调制频率达到180kHz,对数据进行谐波小波处理后获得了高质量的2f信号,该2f 信号的峰值中心辨识度高,其数据光滑度、信号的抗干扰能力方面均优于数字锁相方法。