Autoregressive spectral estimation of fetal breathing movement

Fetal breathing movement (FBM) in utero may be an indicator of fetal health. This paper provides a second-by-second estimate of FBM rate. In the absence of a statistical model for the fetal breathing movement, block data structured autoregressive spectral estimation is used. The optimum tapered Burg algorithm provides a minimum variance breathing rate estimate from a short block of data. The data were recorded using a PVDF (PolyVinyliDeneFluoride) transducer which picks up maternal abdominal wall movements. A peak tracking algorithm is used to extract the fetal breathing rate. Results from these signals are presented in graphical form. Further analysis of the fetal breathing rate has revealed periodicities, similar to that observed in the fetal heart rate.     

激光陀螺信号的小波滤波方法研究

随机噪声是影响激光陀螺精度的一个重要因素,其中随机噪声包括分形噪声和白噪声,采用传统的方法很难去除分形噪声.对于激光陀螺中的随机噪声,利用分形噪声在小波变换域的特殊性质采用小波变换域参数估计方法获得噪声参数;然后采用小波阈值滤波方法去除噪声.对某型号的激光陀螺的滤波结果表明了该方法的有效性.     

1/f类分形信号的最小二乘法参数估计

根据含噪1/f类分形信号的小波变换系数方差随尺度变化的特点,该文提出了一种估计1/f类分形信号参数的新方法,即对其小波系数方差进行简单的变换,使1/f类分形信号参数估计满足最小二乘法参数估计的条件。仿真实验结果表明,该方法可以有效地从加性白噪声背景下估计出1/f类分形信号的,2等参数,从而使1/f类分形信号与加性白噪声分离。     

Multiscale Wiener filter for the restoration of fractal signals:wavelet filter bank approach

A filter bank design based on orthonormal wavelets and equipped with a multiscale Wiener filter is proposed in this paper for signal restoration of 1/f family of fractal signals which are distorted by the transmission channel and corrupted by external noise. First, the fractal signal transmission process is transformed via the analysis filter bank into multiscale convolution subsystems in time-scale domain based on orthonormal wavelets. Some nonstationary properties, e.g., self-similarity, long-term dependency of fractal signals are attenuated in each subband by wavelet multiresolution decomposition so that the Wiener filter bank can be applied to estimate the multiscale input signals. Then the estimated multiscale input signals are synthesized to obtain the estimated input signal. Some simulation examples are given for testing the performance of the proposed algorithm. With this multiscale analysis/synthesis design via the technique of the wavelet filter bank, the multiscale Wiener filter can be applied to treat the signal restoration problem for nonstationary 1/f fractal signals     

Testing (non-)existence of input-output relationships by estimating fractal dimensions

Our aim is to propose tests for (non-)existence of nonlinear relationships between signals, which, after passing a test, can be interpreted as input and output signals of a certain system, if its characteristic is sufficiently smooth. The proposed tests are based on the theoretical results on equality of fractal dimensions of these signals as well as on estimation of fractal dimensions from observations. They are applicable when at least one of these signals has the fractal dimensions strictly larger than one, i.e., it is rough enough. The tests are then verified on simulated data. Their applicability is illustrated by two sets of real data, namely, observations of two financial time series and samples of displacement-force signals in a magneto-hydrological damper.     

分形信号估计的最佳子波门限方法

本文提出了一种基于奈曼－皮尔逊（Ｎｅｙｍａｎ－Ｐｅａｒｓｏｎ）准则和最小均方误差准则的，估计淹没在加性白高斯噪声中的１／ｆ类分形信号的最佳子波门限方法，计算机仿真结果证明了该方法的可行性和有效性。     

Estimation of fractal signals using wavelets and filter banks

A filter bank design based on orthonormal wavelets and equipped with a multiscale Wiener filter was recently proposed for signal restoration and for signal smoothing of 1/f family of fractal signals corrupted by external noise. The conclusions obtained in these papers are based on the following simplificative hypotheses: (1) The wavelet transformation is a whitening filter, and (2) the approximation term of the wavelet expansion can be avoided when the number of octaves in the multiresolution analysis is large enough. In this paper, we show that the estimation of 1/f processes in noise can be improved avoiding these two hypotheses. Explicit expressions of the mean-square error are given, and numerical comparisons with previous results are shown     

立体视频技术的发展现状综述

围绕立体视频产生、编码、传输以及接收显示。就两路光信号产生视差的立体以及两路视频流的编码技术等方面,结合目前业界主流及其热点问题,作了广泛而深入的重点梳理与阐释。指出多视点视频、编码是发展方向。采用运动和视差联合估计,结合如分形编码、小波变换编码等快速算法并应用于最先进的编码标准中,把被动式通用眼镜作为当前一段时间的立体电视过渡,发展到未来的全息立体。     

1/f分形噪声的一种多尺度Kalman滤波方法

针对淹没在1／f分形噪声中的有用信号恢复问题，提出了一种基于小波变换与Kalman滤波的多尺度滤波算法。首先将带有1／f分形噪声的信号分解成多尺度的子带信号，通过小波变换对1／f分形噪声的白化作用，消除了1／f分形噪声的自相似性和长程相关性。然后在小波域内，利用Kalman滤波实现了噪声和有用信号的分离，估计出了各子带中的有用信号。最后进行小波重构，较好地恢复出淹没在1／f分形噪声中的有用信号。仿真实验表明，使用多尺度Kalman滤波器能有效地抑制分形噪声，显著地提高了信噪比。     

A transducer for detection of fetal breathing movements

The paper describes a new transducer for detection of fetal movements and sounds from the maternal abdominal wall. This transducer is based on an inductive principle. The compliance of the transducer should match the compliance of the maternal abdominal wall in order to detect the very weak acoustic signal caused by individual fetal breathing movements. The contact area of the transducer is supported on a membrane, the tension of which can be adjusted so as to match the compliances of tissue and transducer. The goal of this paper is to investigate detection of fetal movements in order to monitor fetal condition and motility. The more specialized field of investigating fetal heart rate variability by studying the relationship between fetal breathing movements and fetal heart rate may become of more interest in the future. The inductive phonometer (INPHO) shows a flat (+/- 1.5 dB) frequency response between 0.2 and 200 Hz which is not affected by the compliance adjustment. Some in vivo measurements have been performed. The transducer signal is stored on a 20MB hard disk of an Olivetti M24 Personal Computer (PC) simultaneously with a control signal indicating the presence of breathing movements. Ultrasound imaging is exclusively used for verification of breathing movements. The images are stored on videotape simultaneously with control signals from the PC for synchronization of data and image. Substantial digital filtering is necessary to discriminate between actual breathing movements and other fetal activities. It is shown that optimal adjustment of the transducer's compliance to that of the maternal abdominal wall is possible and that individual breathing movements can indeed be measured.     

非平稳分形随机信号波形估计的最优门限方法

本文用基于最小均方误差准则的最优门限方法估计叠加高斯白噪声的分形布朗运动,并给出其离散小波变换分解级数确定方法.与多尺度维纳滤波相比,本方法不需估计1/f类分形信号的方差,且其离散小波变换分解级数可预先确定,因此有着更好的实用性和可操作性.     

基于多尺度Wiener滤波器的分形噪声滤波

针对淹没在1/f噪声中的有用信号恢复问题,本文提出了一套基于双正交小波变换与Wiener滤波的多尺度滤波算法,并设计出多尺度Wiener滤波器.首先,利用双正交小波变换将带有1/f噪声的信号分解成多尺度的子带信号,通过小波变换对1/f噪声的白化作用,消除了1/f噪声的非平稳性、自相似性和长程相关性.其次,在小波域内,利用Wiener滤波,实现了噪声和有用信号的分离,估计出了各子带中的有用信号.最后,利用双正交小波的精确重构性,较好地恢复出淹没在1/f噪声中的有用信号.仿真实验表明,该滤波器能有效的抑制分形噪声,显著地提高信噪比.     

基于小波分维的红外图像边缘检测

根据小波变换与分形理论在认识事物的本质上都是基于从总体向局部、从宏观向微观的自相似原理,提出一种以小波作为标尺来定义分维数的思想,将小波变换看作是用小波标尺对信号进行度量,建立一种以信号的细节分量之和作为度量参数的小波分维数.应用小波分维数对红外图像进行边缘提取,实验结果表明该方法简单有效、优于传统的几种边缘提取算子.     

An algorithm for successive identification of reflections

A new algorithm for successive identification of seismic reflections is proposed. Generally, the algorithm can be viewed as a curve matching method for images with specific structure. However, in the paper, the algorithm works on seismic signals assembled to constitute an image in which the investigated reflections produce curves. In numerical examples, the authors work on signals assembled in CMP gathers. The key idea of the algorithm is to estimate the reflection curve parameters and the reflection coefficients along these curves by combining the multipulse technique and the generalized Radon transform. The multipulse technique is used for wavelet identification in each trace, and the generalized Radon transform is used to coordinate the wavelet identification between the individual traces. Furthermore, a stop criterion and a reflection validation procedure are presented. The stop criterion stops the reflection estimation when the actual estimated reflection is insignificant. The reflection validation procedure ensures that the estimated reflections follow the shape of the investigated reflection curves. The algorithm is successfully used in two numerical examples. One is based on a synthetic CMP gather, whereas the other is based on a real recorded CMP gather. Initially, the algorithm requires an estimate of the wavelet that can be performed by any wavelet estimation method.     

Deconvolution filter design for fractal signal transmissionsystems: a multiscale Kalman filter bank approach

A deconvolution filtering design is proposed for the 1/f fractal signal transmission systems, with its design philosophy being based on multiscale Kalman deconvolution filter bank equipped in the analysis/synthesis wavelet filter bank, The role of wavelet transformation for 1/f fractal signal process is exploited as a multiscale whitening filter for removing the properties of self-similarity and long-range dependence from the fractal signals     

Estimation of 2-D noisy fractional Brownian motion and itsapplications using wavelets

The two-dimensional (2-D) fractional Brownian motion (fBm) model is useful in describing natural scenes and textures. Most fractal estimation algorithms for 2-D isotropic fBm images are simple extensions of the one-dimensional (1-D) fBm estimation method. This method does not perform well when the image size is small (say, 32x32). We propose a new algorithm that estimates the fractal parameter from the decay of the variance of the wavelet coefficients across scales. Our method places no restriction on the wavelets. Also, it provides a robust parameter estimation for small noisy fractal images. For image denoising, a Wiener filter is constructed by our algorithm using the estimated parameters and is then applied to the noisy wavelet coefficients at each scale. We show that the averaged power spectrum of the denoised image is isotropic and is a nearly 1/f process. The performance of our algorithm is shown by numerical simulation for both the fractal parameter and the image estimation. Applications to coastline detection and texture segmentation in a noisy environment are also demonstrated.     

基于经验模态分解的光纤陀螺1/fγ类型分形噪声滤除方法

提出了一种可有效滤除输出信号中干扰信号的新的光纤陀螺信号降噪方法.中高精度光纤陀螺的随机噪声中包含了白噪声和具有长程相关性、自相似性及1/fγ型谱密度特点的一种非平稳随机噪声--1/fγ型分形噪声.利用传统的滤波方法无法有效去除该类分形噪声,而新方法以经验模态分解(EMD)和阈值降噪方法为核心,结合提升小波理论对光纤陀螺的输出信号进行软阈值滤波,进而提高光纤陀螺的精度.利用这种新方法对多组实测数据进行滤波仿真实验,结果中仅偏置稳定性一项性能指标就已表明,使用新滤波方法滤波后数据精度可提高一个数量级,而相较传统的小波滤波方法可提高2.5倍,故此验证了新方法的有效性.     

基于小波的2-D分形布朗运动分析与合成

1/f分形随机过程广泛地存在于各种自然现象和社会现象中,日益成为信号检测与估计、信号处理及图像处理的研究热点.分形布朗运动是模拟此类信号的很好的数学模型.小波因其所具有的多尺度分析能力成为分析分形信号的有力工具.本文分析了二维分形布朗运动经小波变换后各尺度间小波系数相关结构的特性,提出了一种合成二维分形布朗运动的算法,并展示了其在和谐图案生成上的应用.     

基于小波和分形理论的调制信号特征提取方法研究

本文针对通信信号这种非平稳的、信噪比(SNR)变化范围较大的信号,应用小波分析和分形理论,提出了有效的特征提取方法,所提取的分形特征包含了区别不同调制类型所需的幅度、频率和相位等主要信息。同时这种特征具有较好的抗干扰特性,基于这种特征的分类器的设计简单、高效。计算机模拟结果表明此方法的有效性。     

Estimation of 1/f signals on the basis of curve fitting

An algorithm is proposed for the identification of fractal signals with wavelet-based models from corrupted data. This algorithm is based on curve fitting and wavelet transformation. It is proved that whenever γ is greater than 0, the algorithm provides an almost consistent estimation. Moreover,the estimated parameters are asymptotically Gaussian distributed. A mean square asymptotic convergence rate of the estimated parameters has also been established. Simulation results verify the efficiency of the proposed algorithm