滑动窗累积量的递推估计算法及其在语音端点检测中的应用

提出了一种滑动窗累积量的递推估计算法并应用于语音端点检测中,用以解决传统端点检测方法在噪声环境下检测性能变差的问题。在对含噪语音信号进行加窗之后,利用滑动窗累积量的递推估计算法估计含噪语音信号的高阶累积量值,并在此基础上结合能量特征进行语音端点检测。实验结果表明,所提滑动窗累积量递推估计算法相比较传统高阶累积量计算方法运算效率明显提高;所提端点检测算法在不同噪声和信噪比环境下相比较G.729b算法点正确率Pc-point值平均提升了6.07%。基于滑动窗高阶累积量的语音端点检测算法具有较高的运算效率及良好的鲁棒性。     

滑动窗累积量的递推估计算法及其在语音端点检测中的应用

提出了一种滑动窗累积量的递推估计算法并应用于语音端点检测中,用以解决传统端点检测方法在噪声环境下检测性能变差的问题。在对含噪语音信号进行加窗之后,利用滑动窗累积量的递推估计算法估计含噪语音信号的高阶累积量值,并在此基础上结合能量特征进行语音端点检测。实验结果表明,所提滑动窗累积量递推估计算法相比较传统高阶累积量计算方法运算效率明显提高;所提端点检测算法在不同噪声和信噪比环境下相比较G.729b算法点正确率Pc-point值平均提升了6.07%。基于滑动窗高阶累积量的语音端点检测算法具有较高的运算效率及良好的鲁棒性。     

电磁场递推算法及微纳光学元件中的应用

提出一种电磁场递推算法来分析微纳光学元件体内电磁场的传输.该方法基于Maxwell方程组和电磁场横向的边界条件给出了严格解.以高斯光束在亚波长矩形浮雕光栅体内的传输为例,分析了非匀幅光束在微纳光学元件体内的传输. 关键词： 递推算法 非匀幅光束 微纳光学元件     

基于滑动窗口子空间的混沌信号降噪算法

基于子空间投影理论，利用混沌信号特性，提出了一种基于滑动窗口子空间投影的混沌信号降噪算法，通过相空间重构和多次迭代运算，较好地解决了低信噪比下的混沌信号降噪问题。对算法的复杂性作了研究，并对重构维数、延迟时间、迭代次数等参数的选择进行了讨论。利用Lorenz模型进行仿真得到了比较好的效果，与传统算法相比，新算法具有降噪效果较好、局部特性损失较少、精度较高等优点。     

A recursive method for calculating the total number of spanning trees and its applications in self-similar small-world scale-free network models

The problem of determining and calculating the number of spanning trees of any finite graph (model) is a great challenge, and has been studied in various fields, such as discrete applied mathematics, theoretical computer science, physics, chemistry and the like. In this paper, firstly, thank to lots of real-life systems and artificial networks built by all kinds of functions and combinations among some simpler and smaller elements (components), we discuss some helpful network-operation, including link-operation and merge-operation, to design more realistic and complicated network models. Secondly, we present a method for computing the total number of spanning trees. As an accessible example, we apply this method to space of trees and cycles respectively, and our results suggest that it is indeed a better one for such models. In order to reflect more widely practical applications and potentially theoretical significance, we study the enumerating method in some existing scale-free network models. On the other hand, we set up a class of new models displaying scale-free feature, that is to say, following P(k) ~ k^?γ, where γ is the degree exponent. Based on detailed calculation, the degree exponent γ of our deterministic scale-free models satisfies γ > 3. In the rest of our discussions, we not only calculate analytically the solutions of average path length, which indicates our models have small-world property being prevailing in amounts of complex systems, but also derive the number of spanning trees by means of the recursive method described in this paper, which clarifies our method is convenient to research these models.     

Fine structure spectrography and its application in speech

A filterbank-based algorithm for time-varying spectral analysis is proposed. The algorithm, which is an enhanced realization of the conventional spectrogram, consists of hundreds or thousands of highly overlapping wideband filter/detector stages, followed by a peak detector that probes the filter/detector outputs at very short time intervals. Analysis with synthetic modulated signals illustrates how the proposed method demodulates these signals. The resulting spectrogram-like display, referred to as a "fine structure spectrogram," shows the fine structure of the modulations in substantially higher detail than is possible with conventional spectrograms. Error evaluation is performed as a function of various parameters of a single- and two-component synthetic modulated signal, and of parameters of the analysis system. In speech, the fine structure spectrogram can detect small frequency and amplitude modulations in the formants. It also appears to identify additional significant time-frequency components in speech that are not detected by other methods, making it potentially useful in speech processing applications.     

A new infrared small and dim target detection algorithm based on multi-directional composite window

This work presents a new method based on gray characteristic analysis for infrared dim small target detection under complex backgrounds. Firstly, an improved detection window with eight directions and three layers is introduced to investigate the gray distribution characteristic of different structure in an infrared image. Secondly, we adopt a pretreatment process based on morphology filter and mean filter to reduce the running time and propose a detection rule on characteristic analysis for infrared targets. Meanwhile a new parameter optimization algorithm based on fuzzy control theory is employed so that the detection rule could be independent of the initial parameters. Finally, experimental results indicate that the proposed method can effectively detect the dim small targets and has better tracking performance.     

Iterative inverse beamforming algorithm and its application in multiple targets detection of passive sonar

With the increasing of detection ability of passive sonar,the weak signal detection problem in multiple interferences becomes more and more important.In the time/bearing record(TBR) display of sonar detection,when there exist traces of multiple interferences,the identification of weak signal is difficult or impossible.The adaptive noise cancellation technique provides the theoretical basis for suppressing strong interferences.But the solution for finding the steady-state optimum filter matrix is quite difficult due to the real time calculation of inverse matrix of input data correlation matrix.The iterative inverse beamforming(IBF) algorithm for solving the optimum filter vector,which is expressed by inverse matrix of the ocean environment data,is derived in this paper,by which,the optimum filter can be eventually expressed as a sum of series simple matrices of constructed from sensor data.Based on the algorithm proposed in this paper,some examples of at sea experiment are provided.The strong interferences are cancelled and the weak signal is emerged,even it didn't appear in the conventional beamforming(CBF) processing.     

一种抗噪分形维计算方法及其在声纳图像识别中的应用

用于计算图像分形维的差分盒计数法(DBC)和鲁棒差分盒计数法(RDBC)都对脉冲噪声和斑点噪声较敏感,为此本文提出一种抗噪差分盒计数法(NRDBC),利用剪切局部标准差(TLSD)来计算图像分形维,由于TLSD可有效滤除脉冲噪声和斑点噪声、且对高斯噪声敏感性小,因此NRDBC能对有噪图像进行可靠的分形维估计。利用多分辨率的DBC、RDBC和NRDBC对混有高斯噪声、脉冲噪声和斑点噪声的7种Brodatz纹理以及3种海底的侧扫声纳图像进行了分类实验,结果表明,本文提出的NRDBC可获得更高的识别率和更好的抗噪性。     

无源声呐多目标检测中反波束成形递推算法及其应用

随着声呐检测能力的提高,多目标干扰下微弱信号的检测问题日益突出。当声呐方位历程显示上出现多个干扰轨迹时,弱目标的检测显得十分困难。自适应噪声抵消(Adaptive Noise Canceling,ANC)技术为抑制多个干扰提供了理论基础,但是求解稳态最佳滤波矩阵存在着技术实现上的困难。
本文提出用一种反波束成形(Inverse Beamforming,IBF)递推算法,在阵元域逐一抵消多个强干扰,从而增强并提取出微弱目标信号。文中给出了递推求解由逆矩阵所表达的最佳滤波矢量的理论推导和相应的公式。利用IBF算法处理海试数据得到了较好的结果,显著改善了强干扰下对微弱信号的检测,甚至在普通波束成形(CBF)中未能显示出来的信号都可以被检测出来。     

切换系统Lyapunov指数的算法及应用

Lyapunov指数是判定系统非线性行为的重要工具,然而目前的大多算法并不适用于切换系统.在传统Jacobi法的基础上,提出了一种新算法,可以直接计算得到n维切换系统的n个Lyapunov指数.首先,根据切换面处相邻轨线的动态变化规律,从相空间几何推导出切换面处轨线变化的Jacobi矩阵;然后,对该矩阵进行QR分解,从而利用R的对角线元素实现Lyapunov指数的切换补偿;最后,将新算法应用到平面双螺旋混沌系统、Glass网络和航天器供电系统三个实例中,并将计算结果与Poincaré映射方法的计算结果进行比较,对新算法的有效性进行验证.     

A universal algorithm for calculating the backscattering factor in Auger-electron spectroscopy

We describe a universal Monte Carlo algorithm that can be used for the efficient calculation of backscattering factors (BFs) for quantitative Auger-electron spectroscopy (AES). This algorithm makes use of the continuous slowing-down approximation and the electron stopping power instead of simulation of individual inelastic-scattering events. This approach is attractive because it can be applied to any material with an empirical formula for the stopping power, available data for differential elastic-scattering cross sections, and an empirical formula for inner-shell ionization cross sections. We report BFs for the Si KL₂₃L₂₃, Cu L₃M₄₅M₄₅, Ag M₅N₄₅N₄₅, and Au M₅N₆₇N₆₇ Auger transitions in the corresponding elemental solids. These BFs were calculated for normal incidence of the primary beam, primary energies from near threshold for ionization of the relevant core levels to 20 keV, and Auger-electron emission angles of 10°, 60°, and 80°. We found satisfactory agreement between these BFs and values obtained from a more accurate algorithm in which individual inelastic-scattering events were simulated. Percentage deviations between BFs from the two algorithms were <2% for Au, <5% for Ag, <7% for Cu, and <10% for Si for primary energies likely to be used in practical AES. These deviations arise mainly from our use of stopping powers from the empirical formula rather than more reliable values calculated from experimental optical data.     

相干噪声快速去除算法及其在声源定位中的应用

针对相干噪声干扰声源辨识问题,将强跟踪滤波器理论与阵列-信号采集模型相结合,发展了一种快速估计相位变化的算法。算法引入多重次优渐消因子,能够进一步提取相位残差中的有用信息,使输出残差序列处处正交,且该因子能根据噪声相位差变化自动调节。通过仿真对连续相位突变进行跟踪表明,在参数失配条件下该算法实现了相位差的准确估计,且其性能在宽频范围具有稳定性。通过音箱实验给出了宽频范围内的成像结果,与已有算法对比表明,该算法不仅能够实时消除噪声干扰并可将收敛速度提高一倍以上。本研究实现了对随机变化相位的准确估计,提升了传声器阵列在相干噪声干扰下的声源实时定位能力。     

一种鲁棒性的最小方差无失真响应波束形成算法及其应用

理论上,自适应波束形成方法要比不依赖于输入数据的常规波束形成方法有更好的目标参数估计能力和干扰抑制能力。但在实际水声环境中,声传播模型、接收阵阵列流形以及信号统计特征等因素往往与实际情况存在一定的差异,导致传统的自适应波束形成方法性能下降。因此,提高自适应波束形成方法对上述因素的鲁棒性变得越来越重要。本文基于最差条件最优化的思想,改进MVDR(最小方差无失真响应)方法的约束条件提出了一种鲁棒性最小方差无失真响应自适应波束形成算法(R-MVDR),并对输入数据协方差矩阵和方向向量存在不确定性的情况进行了性能分析,推导给出了波束形成的加权向量和空间谱估计表达式,最后通过海上实验数据进行了验证。结果证明本文提出的算法在实际环境中有更好的方位分辨能力和干扰抑制能力。     

一种光学探测海底粗糙度的算法及其实验研究

海底微地形粗糙度作为海底沉积物重要的物理性质, 对于海洋工程以及海洋科学考察都有着重要意义, 如何利用光学理论进行海底微地形粗糙度测量, 是近年来该领域研究关注的热点。基于光学中的从明暗恢复形状(shame from shading, SFS)算法, 提出一种快速的海底微地形粗糙度测量算法, 在模型构建同时, 添加水下光传播时的吸收和衰减模型, 测量出海底的微地形, 并用幂律形式进行参数拟合, 以表征粗糙度。仿真证明该算法具有95%的置信度, 是一种适用于海底微地形粗糙度测量的光学算法, 并经过实验验证, 证明其有效性和正确性。     

数字图像相关技术的综合算法及其在断裂力学中的应用

鉴于散斑图的随机噪声和相关搜索运算过程仍是当今影响相关图像技术所获结果精度与计算速度两大有待研究解决的主要问题,提出一种基于小波变换、序惯相似度检测和统计相关算法三者相结合的新算法。其基本原理是应用小波变换对变形前后的散斑图进行滤波平滑处理;利用序惯相似度检测算法进行粗搜索,找到可能的匹配点;在可能的匹配点应用统计相关法进行细搜索,最终找到匹配点的位置。基本实验、计算和应用表明,这种算法在消除噪声和提高运算速度等方面,取得了良好的效果。     

汉语语音的非线性动力学特征及其降噪应用

分析了汉语语音的相关维、最小嵌入维数以及重构相图。分析结果表明汉语语音具有混沌特征。根据这些非线性特征可以有效区分汉语中的浊音、清音和随机噪声,从而可以用于语音降噪。介绍了本地投影法混沌语音降噪的原理与算法,并利用该算法对一些典型的元音和辅音进行降噪,获得了较好的降噪效果。     

听觉计算模型在鲁棒性语音识别中的应用

利用听觉感知机理,建立一个基于听觉感知机理的语音信号特征提取模型。本文由两部分组成,一部分是在传统听觉计算模型基础上提出听觉倒谱特征AFCC(AnditoryFrequencyCepstralCoefficient)的提取方法,这样既压缩了特征维数,减小计算量,又使各个特征维之间相互独立,满足HMM模型的要求。并且根据听觉神经中枢的长时整合特性,文中提出了用低通滤波模型来模拟这种功能。结合该低通模型,提取的语音信号的听觉倒谱特征在HMM框架下取得较好的鲁律性。另一部分在研究听觉侧抑制机理的基础上,提出一个简单有效的听觉侧抑制处理模型。美尔倒谱特征MFCC谱特征经过该侧抑制模型处理,得到侧抑制美倒谱特征MFCCI,实验表明,该新特征MFCCI鲁棒性能比MFCC有大大提高。听觉倒谱特征AFCC经过该侧抑制处理得到侧抑制听觉倒谱特征AFCCI,实验表明,该新特征AFCCI鲁律性能比AFCC有大大提高。     

一种可见光成像的目标检测跟踪方法

在末制导成像阶段目标占据视场的大部分面积,形状信息丰富,这时对目标体上某一固定点的稳定跟踪成为最主要的需求。针对图像灰度过于集中目标难于提取的问题,在图像预处理阶段提出了依据概率统计的图像灰度均衡的方法;为解决图像边角点的快速检测问题,提出了图像二维投影和滑动卷积相结合的方法;最终为实现快速稳定的跟踪,提出了依据角点匹配的形心跟踪方法。根据此算法的特点研制了FPGA+DSP的硬件平台,充分利用FPGA的并行流水特性和DSP的逻辑运算特点,能快速检测到目标形心和进行稳定地跟踪,验证了方法的有效性和实用性。此方法应用在某课题上,跟踪效果良好,为试验的圆满成功提供了保障。     

基于RANSAC的空间圆拟合算法及其在机械手运动检测中的应用

为了实现对水下机械手运动范围的检测,研发了一套多目立体视觉测量系统。通过测量机械手末端空间运动轨迹,利用空间圆拟合算法可计算出被测关节的实际运动范围。对其中的核心算法空间圆拟合进行了研究。首先空间圆可看作是由一个平面与球体相交而成,其圆心必定在球体上任意两点连线的中垂面上,可基于空间向量的拟合方法推导出中垂面的方程,与拟合的空间平面联立即可求出空间圆方程,进而利用拟合出来的空间圆的圆心坐标求出圆半径。然后对实际测量过程中的错误跟踪点进行了分析,如果在空间圆拟合的过程中对错误跟踪点不加以去除,则会带来错误的拟合结果,从而会大大影响测量结果的正确性。最后提出了基于RANSAC(Random Sample Consensus)的空间圆拟合算法,它可以从一组包含错误点的测量数据集中通过迭代方式有效剔除粗大误差点,从而估计出数学模型的参数和正确的拟合结果。仿真测试及实际测量实验的结果表明,当粗大误差点所占总测量点数的比例小于20%时,所提出的算法可有效地剔除所有粗大误差点,很好地解决了机械手运动范围检测系统在实际工程应用中所遇到的问题。