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spectral density相关的网络例句

查询词典 spectral density

与 spectral density 相关的网络例句 [注:此内容来源于网络,仅供参考]

Extract information based on the instantaneous features : In the center is one of the instantaneous rate of the power spectral density of the maximum, is a center to the absolute value of the instantaneous rate of the standard deviation, Non-zero weak signal instantaneous phase of the nonlinear component absolute standard deviation, Non-zero weak signal instantaneous phase of the nonlinear component standard deviation, In the center is one of the non-weak signal of the absolute value of the instantaneous frequency standard deviation, a signal to one of the instantaneous frequency of the power spectral density of the maximum, According to 16QAM and QPSK signals XI axis projection in the different performance parameters raised.

提取信号七个基于瞬时信息的特征:零中心归一化瞬时幅度功率谱密度的最大值,零中心归一化瞬时幅度绝对值的标准偏差,零中心非弱信号段瞬时相位非线性分量绝对值标准偏差,零中心非弱信号段瞬时相位非线性分量标准偏差,零中心归一化的非弱信号段瞬时频率绝对值的标准偏差,一个信号段的归一化瞬时频率功率谱密度的最大值,根据信号 QPSK 和16QAM在 XI 轴投影的不同表现,提出特征参数。

In order to represent accurately and concisely the changing characteristics of one-dimensional spectrum density function in the chatter development. This thesis, for the first time, proposes the Edgeworth asymptotic expansion formulas of spectral density. A detailed proof is given. Some new statistic including spectral skewness, spectral kurtosis and spectral cumulants are proposed.

为了准确、简洁地表达一维谱密度函数在切削颤振建立过程中的变化特征,论文首次建立了一维谱密度函数的Edgeworth渐近谱展开式,给出了详细的证明;并由此提出了"谱偏态系数"、"谱峰态系数"和"谱累积量函数"等新的谱统计量。

School of Electronic and Information Engineering,Dalian University of Technology,Dalian,Liaoning 116024,ChinaStable processes can better model the impulsive random signals and noises in physical observation.This paper briefly describes its spectral representation,proposes a new different spectral density from power spectrum density of second order processes,thus can get a new concept of stable white noise based on covariation spectrum,and a method of identification of nonlinear PAR system based on least p-norm.

描述了稳定分布的谱表示,提出了共变谱密度的概念,得到一种基于自共变序列与共变谱的稳定分布白噪声与有色噪声的概念及其判断标准,对传统意义上的白噪声进行了广义化,依据多项式自回归系统模型,对基于稳定白噪声输入的系统输出非线性稳定有色噪声建立其非线性PAR模型,提出基于最小P范数的EIRLP算法对非线性PAR系统进行辨识。

A method of cross power spectral density between responses is derived and a poly reference modal analysis method using cross power spectral density method in frequency domain is presented in this paper.

对各测点响应的互功率谱密度函数进行了详细推导,提出了一种基于互功率谱密度的频域多参点辨识法,这意味着许多原本利用频响函数的传统频域识别法可以很容易地用于工作状态下的模态识别,大大开阔了未知激励下模态识别的视野。

PSD method for identifying cross power spectral density of distributed excitation force is discussed by calculating cross power spectral density of measured response.

功率谱密度函数识别法则是以系统反应之交叉功率谱密度函数识别外力之交叉功率谱密度函数。

Its fluctuation property is qualitatively characterized by the power spectral density and integral spectral density,and it is concluded that the ratio of high frequency phase noise increases with the increase of pump power.

利用功率谱、积分谱对具体泵浦条件下的相位噪声特性进行定性分析,结果表明,泵浦功率越大,高频成分占的比例越大。

Aiming at the complexity of data used by tradition method, the new method firstly extracted key points-unstructured data of position and scale stabilization from circum-rectangle area of human body,computed power spectral density of key point; Then obtained distribution of power spectral density of key point; finally judged human movement state form its distribution characteristic.

针对传统人体状态检测方法利用数据信息的复杂性,对图像中人体外接矩形区域提取位置和尺度稳定的非结构化数据信息——关键点,计算关键点的功率谱密度,在序列视频图像中可获得关键点功率谱密度的分布,利用其分布特点判断人体运动状态。

Estimation of spectral densities for single and multiple time series. Nonparametric estimation of spectral density, cross-spectral density, and coherency for stationary time series, real and complex spectrum techniques.

时间序列谱分析:单个和多个时间序列的谱密度估计,谱密度的非参数估计,交叉谱密度,静态时间序列的一致性,实时和复杂的谱技术,双频谱Bispectrum。

It is found that there are no obvious corresponding signals related to the Slichter modes claimed by Smylie (1992), Smylie et al.(1993) and Courtier et al.(2000) in the product spectral density estimates. Instead, it is found that there exist 8 common significant spectral peaks in the subtidal band in the product spectral density estimates of the SCG gravity data, which may be related to some unknown global geodynamical or geophysical effects. It is very encouraging that the central periods of three peaks of them are estimated accurately as 4.93438 ±0.00186h, 4.42734 ±0.001159h and 4.09269 ±0.00082h, respectively, and in significant accordance with the eigenperiod of the Slichter modes of the solid inner core expected theoretically by Smith (1976) with only differences of 0.4%,-1.4% and 1.0%, respectively.

初步分析结果表明,在积谱密度估计中没有Smylie(1992),Smylie等(1993)和Courtier等(2000)发现的与内核平动振荡有关的共振信号,但存在与某些未知的全球地球物理或地球动力学效应有关的8个重要的明显公共谱峰,估计了在这些谱峰附近的重力共振参数,其中三个谱峰的中心周期与Smith(1976)理论预测的固体内核Slichter模的本征周期符合得非常好,二者之间的差异分别仅为0.4%,-1.4%和1.0%。

This paper introduces a novel technique for estimating the signal power spectral density to be used in the transfer function of a microphone array post-filter.The technique is a modification of overestimation of noise power spectral density of the existing Zelinski post-filter and McCowan post-filter,which utilize the auto- and cross- spectral densities of the signals.Near-field compensation is taken into account.

介绍了一种用于近场麦克风阵列后滤波语音增强的方法,避免了现有的利用自功率谱密度和互功率谱密度的Zelinski和McCowan后滤波器中噪声功率谱过估计的问题,并加入了近场传播的幅度衰减补偿和相位延迟补偿。

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