随机信号

基于B样条函数的多尺度随机信号处理系统研究

Study of System in Multiscale Random Signal Processing Using B-Spline Function

一种基于DSP的任意功率谱随机信号产生器

A DSP based system for generating random signal with specified power spectrum

随机信号实时重构的快速算法及其DSP实现

A Fast Realtime Reconstruction Algorithm of Random Signal and DSP Realization

随机信号的功率谱估计及Matlab的实现

PSD ( Power Spectrum Density ) Estimation for Random Signal and Realization in Matlab

论文针对非平稳随机信号AR模型的实时建模理论和方法进行了深入研究，研究了多种非平稳随机信号的实时建模方法并对之进行分析比较。

So various modeling methods for non-stationary stochastic signals are researched .

随机信号AR频谱模型的本质研究

Study on essence of AR spectrum model for random signal

相关噪声中随机信号的Robust因果Wiener滤波

Robust Causal Wiener Filtering for Random Signal in Correlated Noise

基于Kalman光纤陀螺的随机信号处理

Based on Kalman Filter Processing of FOG Signal

序流程图，在分析、处理随机信号逻辑关系的基础上，提出了PLC的编程方法。

After analyzing and processing the logical relationship of stochastic signal , the way of PLC program is put forward .

本文提出了一种二次加窗LMS自适应时间延迟估计方法，适用于带限平稳白色随机信号的时间延迟估计。

An LMS adaptive time delay estimation method with two windows is presented .

一类带Gauss白噪声的随机信号传递系统的优化建模与系统分析

Modeling and analysis of a kind of stochastic signal transfer systems with Gauss white noise

隐马尔科夫模型（HiddenMarkovmodel，简记为HMM）作为一种统计模型，在模式识别与随机信号处理中有着广泛的应用。

As a statistics model , Hidden Markov Model ( HMM ) have been widely used in pattern recognition and stochastic signal processing .

EMD在非平稳随机信号消除趋势项中的研究与应用

Research on and Application of EMD in Eliminating Trend Item of Non-stationary Random Signals

随机信号Haar小波包变换的性能研究

Performance Analysis of Haar Wavelet Packet Transforms to Random Digital Signals

对随机信号用此方法进行功率谱估计，估计性能明显好于经典的Welch功率谱估计。

The method is also better than Welch power spectrum estimate .

Fourier分析在处理平稳随机信号方面有着不可替代的作用，而大量的现实存在的信号是非平稳时变的信号，这样Fourier分析显得能力不足。

Fourier analysis is an irreplaceable tool on processing stationary stochastic signals , but is at a loss on processing non-stationary time-varying signals that abound in real world .

本文主要介绍可编程序控制器（PLC）技术在电梯领域的应用，在分析、处理随机信号逻辑关系的基础上，提出PLC的编程方法。

The article mainly introduces application of PLC technology in higher building elevator control system . After analyzing and processing the logical relationship of stochastic signal , the ways of PLC programming is put forward .

本文首先介绍非平稳随机信号及其主要研究方向，对TVAR参数模型进行详细剖析。

This paper firstly introduced nonstationary random signal and its research direction .

混沌调频信号类似随机信号，具有较强的抗干扰性能（ECCM）。

Chaotic FM signal is similar to random signal . It has good Electronic Counter-Counter Measure ( ECCM ) capabilities .

实验后分别计算分析实验样本的积分肌电值（IEMG）和功率谱中值频率（MF）。随机信号中值频率实时估计的研究

IEMG and MF were calculated and analyzed after the task . Research on the estimating median frequency of random signal power spectrum in real time

该方法应用改进冗余位结构，通过在其子DAC输出端引入伪随机信号测量级间增益，并利用此估计值在后台进行增益误差补偿。

Using a reformative redundant stage , gain errors are measured by PR ( pseudo-random ) signal being injected at sub-DAC output and compensated in background according to the estimated value .

本文利用MATLAB程序来产生所需的随机信号，并通过动态数据交换技术（DDE）与控制软件共同构成随机控制平台。

The random control signals was generated by MATLAB programs and then was send into the control software by using DDE ( dynamic data exchange ) . So the control platform was established by the two software .

指出：室性心动过速（VT）和心室纤颤（VF）是不同于随机信号的，是具有复杂非线性特性的混沌信号。

It is pointed out that ventricular tachycardia ( VT ) and ventricular fibrillation ( VF ) are complex nonlinear chaotic signals , which was proved different from stochastic signal .

微机械陀螺非平稳随机信号改进GM-AR模型研究

An improved GM-AR model for a micromechanical gyroscope 's nonstationary random signals

对旋转不变技术估计信号参量的方法进行了深入的分析，并进而提出了有色声随机信号背景下互谱TLS-ESPRIT估计方法。

Based on further analysis of signal estimation for signal via rotational invariance techniques , a novel cross-spectral TLS-ESPRIT method in colored stochastic noise is proposed .

在Kirchhoff衍射理论的基础上，应用随机信号相关原理，推导了作刚体运动的界面上反射超声散斑在空间运动时，保持其复振幅相关的必要条件。

Based on the Kirchhoff diffraction theory , the necessary condition for keeping the correlation of the complex amplitudes of the ultrasonic speckles back scattered from an interface in rigid body motion is deduced by applying the correlation principle .

研究了非高斯噪声中具有未知参数的信号的渐进最优检测，应用非高斯噪声中线性模型信号以及随机信号的Rao检验，导出了Rao检测的解析式，并与广义似然比检验的性能做比较。

Insensible optimal detection method of unknown parameter signal in non-Gaussian noise is introduced . The analytic expression of Rao detection is presented based on the Rao detection of linear signal and random signal in non-Gaussian noise .

对田间试验结果进行频谱分析和滤波处理后，分析表明土壤机械阻力是低频随机信号，主频集中在2Hz以内；

After spectrum analysis and filtering , the results showed that soil mechanical resistance is lower frequency signal and the lower spectrum density occurs at 2Hz ;

基于时间结构的独立成分分析法（ICA），先后对随机信号和实际雷达信号进行了独立成分分析处理，以增加独立样本数。旨在以更少的扫描时间，得到相同精度的探测数据。

Based on independent component analysis ( ICA ) algorithm , this paper analyzes and processes the random signals and real radar signals successively , which is designed to increasing the number of individual samples and get the sounding data of the same precision in less scanning time .

时变自回归（TVAR）参数模型具有良好的参数压缩性和高分辨率特性，是近年来分析和处理非平稳随机信号的一种有效的方法。

In recent years , the time-varying parametric model , especially time-varying auto-regressive ( TVAR ) parametric model is used to describe a nonstationary random signal widely for its parsimony and high resolution .