一个小波函数指数参数变化的分岔现象

研究一个高斯小波函数产生的混沌分岔现象.随着小波函数中指数参数的增加，它的分岔图出现了倍周期分岔，然后出现混沌，经过一段混沌区域后又出现2的幂周期.在整个过程中，正分岔与逆分岔完整地结合在一起.改变小波函数的系数出现一些明显的奇数周期，如3周期、5周期等.绘制Lyapunov指数曲线及映射折射过程，对混沌现象进行研究.将小波函数展开成近似的多项式函数，对近似多项式函数的分岔图进行了分析. 关键词： 混沌 分岔 小波函数     

Wavelet method applied to specific adhesion of elastic solids via molecular bonds

We propose a wavelet method to analyze the stochastic-elastic problem of specific adhesion between two elastic solids via ligand-receptor bond clusters, which is governed by a nonlinear integro-differential equation with a singular Cauchy kernel to describe the mean-field coupling between deformation of elastic materials and stochastic behavior of the molecular bonds. To solve this problem, Galerkin method based on a wavelet approximation scheme is adopted, and special treatment which transforms the singular Cauchy kernel into a smooth one has been proposed to avoid the cumbersome calculation of singular integrals. Numerical results demonstrate that the method is fully capable of solving the specific adhesion problems with complex nonlinear and singular equations. Based on the proposed method, investigations are performed to reveal the relation between steady-state pulling force and mean surface separation under different stress concentration indexes, which is crucial for assembling the overall constitutive relations for multicellular tumor spheroids and polymer-matrix microcomposites.     

Treatment of MZI sensor signal with an improved wavelet neighboring coefficients

In order to gain the wavelength drift of Mach–Zehnder interferometer (MZI) sensor system, achieve the measurement of ambient environment parameters precisely, so, need to treatment optical fiber sensing signal with noise. Firstly, introduce the method of neighborhood wavelet coefficient by analyzing the drawback of traditional wavelet de-noising methods. Secondly, an improved threshold is putted forward based on neighboring coefficients in this paper which is to overcome the shortcomings of traditional wavelet methods. Finally, the threshold function proposed by this paper deal with MZI sensing noisy signal together with improved threshold. The simulation result shows that the new method can get the better signal-to-noise ratios (SNR) and root of mean square error (MSE) simultaneously and gain the reconstruction signal of the higher correlation coefficient (CC). Compared with the soft and hard threshold method, its SNR increases by 2–4 db, and compared with NeighCoeff, its SNR improves by 1.2 db. The peak error is 1.6 pm. So, the system can meet the requirement of improving sensor detection precision.     

Hand gesture pointing location detection

Gesture recognition has been implemented in many systems for different purposes. The way it is used can be different from system to system. Few used them as touch objects using sensors while few use them as pointing object where the camera is in front of the hand, but the location is being pointed by human, can be detected only if the camera is behind that person. This paper presents an automatic system to detect the location on the wall where the user is currently pointing by his hand. This is done with the detection of head and both hands. The shoulders and elbows’ locations are identified using geometry analysis to understand the current gesture of the human and finally the direction where user hand is pointing would be detected. The face was detected using Haar classifier and shoulders were estimated using the rectangle method near the head. This method does not work in poor illumination conditions and is made to detect only one person at a time. Also user is supposed to wear half sleeve or sleeveless shirt for the better segmentation.     

Analysis of Lau interferometric fringe for measurement of focal length by using wavelet filtering techniques

New filtering scheme is investigated and implemented on Lau interferometric fringes to enhance the signal-to-noise ratio (SNR) in the Lau interferograms. Towards this, the applicability of Haar, Daubechies and Symlet wavelet based filtering schemes have been tested. Of these schemes, the Symlet based filtering scheme gives the best results in terms of improved signal to noise ratio and speckle index. This scheme is then used to analyse Lau interferograms recorded in the experimental arrangement for focal length measurement. The processed interferograms yield improved accuracy and precision of measurement.     

基于LAMOST光谱的恒星大气物理参数估计

基于实测光谱的恒星大气物理参数估计是探索恒星本质的首要任务。随着郭守敬望远镜(LAMOST)进入正式巡天阶段,正以前所未有的速度获取海量的恒星实测光谱数据,这为星系研究带来了新的机遇和挑战。由于LAMOST是多目标光纤光谱天文望远镜,获取的光谱噪音比较大。光谱前期处理中的波长定标和流量定标精度不高,导致光谱存在微小畸变,这些都大大增加了恒星大气物理参数测量的难度。如何对LAMOST实测光谱的恒星大气物理参数进行自动测量是迫切期待需要研究的一个重要课题,关键是如何消除噪声,提高恒星大气物理参数的测量精度和鲁棒性。提出了一个测量LAMOST恒星光谱大气参数的回归模型(SVM(lasso))。基本思路是:首先使用Haar小波对光谱信号进行滤波,抑制光谱中噪声的不利影响,最大限度地保留光谱判别信息。然后采用lasso算法进行特征选择,选取与恒星大气物理参数相关性强的特征。最后将选择的光谱特征输入支持向量机回归模型对恒星大气物理参数进行估计,该模型对光谱畸变和噪音的容忍性比较好,提高了测量的精确度。为了验证上述方案的可行性,在33 963条LAMOST先导巡天恒星光谱库上作了实验研究,三个恒星大气物理参数的精度分别为log Teff:0.006 8dex,log g:0.1551dex,[Fe/H]:0.104 0dex。     

交通流突变点的无标度特征分析

交通流时间序列在不同时间尺度上具有不同的波动特征.为了分析交通流的突变特征,以一段实际的交通流量序列为研究对象进行实证研究.采用小波变换的方法求得交通流在不同尺度上的突变点,按照小波函数过零点数目将交通流的尺度划分为若干层次,并分析了交通流突变的层次性.计算表明:以突变点数目为测度时,在一定的尺度范围内,交通流在突变层次上的突变点数目满足自相似性特征.因此,交通流的突变在不同尺度上具有无标度性.     

碎片云超高速撞击声发射信号特征分析

为了掌握带防护屏的航天器结构受空间碎片超高速撞击时的声发射信号特征,利用二级轻气炮发射球形弹丸撞击铝合金双层板结构,获取了碎片云撞击铝合金板舱壁产生的声发射信号,并利用小波包技术和能量熵理论对信号进行了分析。实验结果表明:弹丸初始速度、防护屏厚度及弹丸直径是决定二次碎片云形态及声发射信号特征的重要因素;在本实验工况范围内,小波包能量熵值能够描述声发射信号频率的复杂程度;当弹丸初始速度处于破碎段(3~7km/s)时,随着初始速度的增大,二次碎片云进一步细化,撞击产生的声发射信号幅值趋于减小、频率成分趋于复杂化,其小波包能量熵值逐渐增大;防护屏厚度对声发射信号的小波包能量熵值影响较大,弹丸直径对其影响较小。研究结果有助于实现对碎片云撞击舱壁结构的损伤模式识别。     

基于双树复数小波变换的微钙化诊断方法

提出一种基于双树复数小波变换的微钙化分类方法.通过提取基于小波和灰度直方图的纹理特征,结合遗传算法进行特征优化,分别用神经网络,支持向量机和KNN分类器进行微钙化的良恶性分类.对三种不同的分类器进行对比,结果表明:KNN分类器取得最好的效果,而支持向量机优于神经网络.KNN分类器对比于神经网络和支持向量机,无需训练,可节约训练时间,最直接地利用了样本和样本之间的关系,减少了类别特征选择不当对分类结果造成的不利影响,可以最大程度地减少分类过程中的误差项.在类别决策时,KNN分类器只与极少量的相邻样本有关,可以较好地避免样本数量的不平衡问题.与传统的小波比较,双树复数小波具有近似平移不变性和正则性,对图像信号具有良好的方向选择性,且冗余度有限,计算量较小.     

复轮廓波包的构造及其图像去噪应用

一般的轮廓波变换只对信号的低频部分进行分解,却忽略了信号的高频部分,因而丢失了丰富的细节和纹理信息,为了克服这种缺陷,本文利用解析的双树复小波包变换和非抽样方向滤波器组,构造了复轮廓波包变换,并提出一种基于相邻系数阈值分类的复轮廓波包图像去噪算法.新的变换除了具有多分辨率、局部性、多方向性和各向异性的特点外,还具有平移不变性和更丰富的方向分量.仿真试验结果表明,构造的复轮廓波包变换能够有效地抑制伪Gibbs现象,并且保护更多的边缘和纹理等细节,其PSNR值和视觉质量均优于一般的去噪方法.