提出了一种基于高阶统计量的图像识别算法。
A new image recognition method using higher order statistics is proposed.
提出了一种基于图像高阶统计量的识别算法。
A new image recognition method based on high-order statistics is proposed.
提出了一种基于高阶统计量调制的数字传输技术。
A digital transmission technology based on high - order statistics modulation has been proposed in this article.
表明高阶统计量方法可以有效地抑制有色噪声的影响。
It is shown that the higher order statistics approaches restrain effectively the effect of coloured noise.
第六章研究了高阶统计量在晶体管低频噪声检测中的应用。
In chapter six, the application of higher order statistics in detection low-frequency noise of transistor is discussed.
采用了高阶统计量与低阶统计量相结合为度量的背景提取算法。
The background obtainment algorithm USES high order statistics and low order statistics.
提出了一种利用高阶统计量对强噪声背景下的弱信号进行检测的方法。
A method on weak signal detection in a stronger noise background based on high-order statistics is presented in this paper.
该方法的关键是依据高阶统计量原理，分析地震信号的高阶统计量特征。
The key of the method is to analyze the feature of high order statistic of seismic signal based on high order statistic.
基于高阶统计量技术，提出了一种气液两相流差压波动信号分析的新方法。
The main works are listed as follows:1) Based on higher-order statistics technique, a new method for differential pressure fluctuation signal analysis of gas-liquid two-phase flow is proposed.
提出了一种基于高阶统计量分析的相位误差估计算法，用于SAR图像自聚焦。
In this paper, a new method of phase errors estimation based on higher order statistics is proposed for SAR imagery autofocus.
经过与井资料反演和高阶统计量分析结果对比验证，证明了本方法储层预测的可行性。
Compared with the results of logging inversion and higher order statistics, this method is proved to be feasible in reservoir prediction.
本文重点研究了统计性方法中，基于高阶统计量及混合蚁群算法的地震子波估计方法。
This paper studies a statistical seismic wavelet estimation method, which based on higher order statistics and the hybrid ant colony algorithm.
提出的用高阶统计量法求取的地震子波，比用常规方法提取的子波更接近真实的地震子波。
This paper proposes the higher order statistics method by which the seismic wavelet taken is more similar to the real seismic wavelet taken by the conventional method.
高阶统计量在信号处理中成功的应用例子之一是估计高斯相关噪声中非高斯信号的时延参数。
One of the primary applications of higher order statistics has been for the time delay estimation of non-Gaussian signal in Gaussian spatially correlated noise.
在许多盲信号源分离算法中，大多需要选择合适的非线性函数或者需要计算信号的高阶统计量。
In many algorithms for blind source separation, most of them must select nonlinear function or compute high-order statistical values.
本文分析了盲均衡准则，阐述了高阶统计量的基础知识，总结了基于高阶统计量的几种盲均衡算法。
This paper researches blind equalization ruler, analyses the knowledge of HOS and summarizes some algorithms based on the HOS.
介绍了高阶统计量与互相关运算相混合的方法，在对非高斯相关噪声中，高斯信号进行时延估计中的应用。
A new hybrid approach to solve the time delay estimation of Gaussian signal in the presence of unknown non-Gaussian spatially correlated noise has been proposed.
利用高阶统计量模糊神经网络方法对液压系统故障进行诊断，解决低信噪比故障特征信号下的故障诊断问题。
A method to diagnose the fault of the hydraulic system based on the high order cumulant fuzzy neural network method is presented.
利用随机变量的各阶矩的性质，构造了一种基于高阶统计量的背景估计方法，并将其应用于静态背景下的运动目标检测。
An approach of background estimation is presented using characters of random variable moments and applied in moving object detection under static background.
该方法利用原图像的均值图像设计编码码书，利用高阶统计量对域块进行分类，可以有效地减少域池中域块之间的相关性。
This method USES the mean image to generate the domain pool, then, classes the domain blocks according to their high order statistics.
针对加性高斯有色噪声背景下的一维、二维线性调频信号的参量估计问题，引入高阶统计量，提出了一种基于四阶累积量的新方法。
For the problem of parameter estimation of one dimensional and two dimensional chirp signal in additive colored Gaussian noise, a new method based on fourth-order cumulant is proposed.
文章首先介绍了高阶统计量的定义和性质，特别指出了高阶统计量对高斯过程不敏感，这是我们利用它进行信号检测和估计的理论依据。
First, the definition and properties of HOS are introduced. We especially notice that HOS is insensitive to Gaussian process. This is the theoretical basis of signal detection and estimation.
本文利用高阶循环统计量讨论几乎周期滑动平均(apma)信号参数的闭式递推估计。
This paper deals with the closed form recursive estimation for parameters of almost periodic moving average (APMA) signal using higher order cyclic statistics.
本文利用高阶循环统计量讨论几乎周期滑动平均(apma)信号参数的闭式递推估计。
This paper deals with the closed form recursive estimation for parameters of almost periodic moving average (APMA) signal using higher order cyclic statistics.
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