本文概述了数字滤波和时间序列分析在地震前兆信息处理中的应用。
Application of digital filtering and time series analysis to earthquake precursory processing is summarized in this paper.
可分为四个主模块：信号来源模块、滤波处理模块、FFT模块和序列基础运算模块。
It contains four main modules: signal producing and simulating, FFT, digital filter and basic mathematical operation.
本文利用时间序列谱分析和卡尔曼滤波的方法讨论了两个随机过程，主要是自回归滑动平均(ARMA)过程，的叠加问题。
Using the methods of time series spectral analysis and Kalman filter, this article discussed the additive problems of two stochastic processes, mainly Auto Regression Moving Average (ARMA) processes.
针对该问题，提出了利用目标航向机动序列修正传统跟踪算法滤波值的新算法。
The algorithm can be used to adjust the filtering results of a traditional algorithm with targets course maneuvering series.
在加权最小二乘的基础上，结合PDE正则化，提出了一种视频图像序列超分辨率重建的自适应滤波方法。
An adaptive filter for video image sequence super resolution reconstruction is proposed on the basis of the weighted least square and PDE regularization in this paper.
为了提高红外图像序列中弱小目标的信噪比和检测概率，同时考虑检测算法实时性，提出了一种新的基于空时域滤波的小目标检测方法。
To improve the Signal-to-noise Ratio(SNR) and detecting probability of small target in infrared image sequences, a novel method of target detection based on spatial-temporal filtering is proposed.
在对激光陀螺漂移数据建立时间序列模型的基础上，对激光陀螺的漂移数据进行了卡尔曼滤波。
The paper sets up a time sequence model of laser gyro random error and processes the drift data by Kalman filter based on the model.
将板形检测信号视为动态时间序列，运用自适应滤波理论，建立了一种通用的板形检测信号除噪方法。
Flatness detection signal was looked on as dynamic time series and by the theory of adaptive filtering a general method was developed to remove the harmful noise from the flatness detection signal.
为了解决低对比度红外序列图像中运动小目标的检测问题，提出了一种基于多级滤波的检测方法。
In order to solve the problem of detecting moving small targets in low-contrast infrared image sequences, a new detection method based on multilevel filter is proposed.
以新息序列的平均平方和为评价函数优化扫描光谱的峰位，消除扫描过程中可能产生的波长定位误差，从而保证滤波结果的准确性，并使实际检出限显著改善。
The whiteness of the innovation sequence for an optimal filter was explored to be the criterion for the correction of the wavelength positioning errors which may occur in spectral scans.
根据运动背景下运动小目标的特点，提出自适应背景对消滤波法。该方法利用图像序列的相关性来检测目标。
Based on the feature of moving target in moving background, adaptive background cancellation filtering method is presented, in which target is detected by use of correlation of image sequence.
根据目标、背景干扰和噪声在红外序列图像中的差异，提出了一种基于空间高通滤波和时间域上N帧轨迹积累的运动小目标检测方法。
According to the imaging difference of target, background clutter and noise, a moving small target detection method based on spacial high-pass filtering and N-frame track accumulating is presented.
实验结果表明：正常肺音音源为白噪声，异常肺音音源为周期脉冲序列，肺胸系统相当于声低通滤波器。
The results of experiment show that dreath sound sources are random white noise, Abnormal breath sounds sources are sequence of periodic impulses.
为提高含噪视频序列的质量和效果，提出一种基于开关噪声检测与三维中值滤波相结合的开关3 -D中值滤波算法。
To improve the quality and effect of video sequences with noise, this paper proposes a switching 3-d median filter algorithm combining noise detection and 3-d median filter.
结合图像的色彩分布和空间布局，提出了一种基于HSV色彩和空间信息的序列蒙特卡罗滤波人脸跟踪算法。
Incorporating color distribution and spatial layout, this paper proposes a sequential Monte Carlo filter tracking face algorithm using color and spatial information in HSV color space.
水印对剪切、JPEG有损压缩、中值滤波、抵抗噪声干扰等常规图像处理手段比较其他的随机序列扩频算法具有更好的鲁棒性。
Compared with the other spread spectrum algorithm, this one is more robust against the typical image processing attacks such as adding noise, filtering and JPEG compression.
文中提出了四种可行的组合滤波脉冲序列，并以WEFT与1—3之组合为例，给出了具体说明和实验结果。
Four reasonable pulse sequences of combined filter method were designed. An explanation and experimental result for the combination of WEFT and 1-3-3-1 is shown.
讨论了滤波器中时间序列的短时分形盒维数的定义及分形模糊控制函数形式及选用方式。
The definition of short-time fractal box dimension and the fuzzy control function of the filter are discussed.
码序列的区分是通过匹配滤波器完成的，通过检测输入数据流中特殊的码序列可以区分不同的移动终端。
This discrimination is accomplished by means of a matched filter, whose output indicates when a particular code sequence is detected in the input data stream.
结合现代时间序列分析方法，并根据新息模型设计了状态最优滤波器。
An ARMA innovation model and the state optimal filter are designed by modern time series analysis method.
在视频图像获取过程中，由于噪声对图像序列的降质，需要设计实时噪声滤波器。
For the degradation of image sequence due to noise, the temporal noise filter is designed during video image acquisition process.
本文依据卡尔曼滤波器在使用最佳增益时，其余差序列互不相关的性质，开发了一种新的渐消滤波算法。
A new fading filtering algorithm is developed based on the property of Kalman filter that the sequence of residuals is uncorrelated when the optimal gain is used.
基于混沌动力系统相空间的延迟坐标重构和双线性表达式，设计了预测混沌时间序列的双线性自适应预测滤波器。
Based on the delay-coordinate reconstruction and bilinear expressions in the phase space of a chaotic system, a bilinear adaptive filter was designed to predict low-dimensional chaotic time series.
本文采用有限精度非线性数字滤波器结构设计混沌跳频序列发生器。
In this paper, a finite precision chaotic FH sequence generator is designed based on the structure of digital filters.
设计强跟踪滤波的思想是：使得残差序列在每一步相互正交，提取残差序列中所有有用的信息，用作对现时刻系统状态的估计。
The idea of the filter is to make discrepancy orthogonal at each step and get useful information from the discrepancy series as current state estimation.
该算法以小波变换中的滤波器理论为基础，通过将图像序列在时间域的尺度分解和相应统计量计算，获得在红外焦平面校正中起影响的偏置和增益系数。
With the scale decomposition of image sequences on the time field and the corresponding statistics' calculation, the offset and gain coefficients in IRFPA NUC were obtained.
并提出了通用的最佳混沌扩频序列设计方法，即利用数字IIR滤波器滤波混沌序列产生最佳混沌扩频序列。
A general methodology for the design of optimal chaotic spreading sequences by using chaotic sequences filtered by digital IIR filter is provided.
本文用现代时间序列分析方法，对于通过已知线性系统被观测的未知多变量arma信号，提出了一种新的自校正去卷滤波器。
Using the modern time series analysis method, this paper presents a new self - tuning deconvolution filter for unknown multivariable ARMA signal observed through a known linear system.
最后对分割结果进行了形态滤波，以此来消除杂点等，恢复出图像序列中的运动前景。
Finally, we performed morphological filtering on the segmentation results, in order to eliminate the miscellaneous points and restore the moving foreground of the image sequences.
最后对分割结果进行了形态滤波，以此来消除杂点等，恢复出图像序列中的运动前景。
Finally, we performed morphological filtering on the segmentation results, in order to eliminate the miscellaneous points and restore the moving foreground of the image sequences.
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