Stationary time series state space modeling method for the analysis of the transition process gyro.
将非平稳时间序列的状态空间建模方法用于陀螺过渡过程的分析。
The dynamic measurement is a non stationary random process varying with the measuring time. The dynamic measuring data have the characteristics of time variation, randomness, correlation and dynamic.
动态测量是随测量时间而变化的非平稳随机过程，动态测量数据具有时变性、随机性、相关性和动态性四个基本特性。
Usually, ionospheric Total Electron Conten (TEC) variation with time can be viewed as a stationary random process under quiet conditions.
平静状态下电离层总电子含量(TEC)随时间的变化通常可以视为平稳随机过程。
We consider asymptotic behaviors of stationary tail probabilities in the discrete time quasi-birth-and-death (QBD) process with a countable background state space.
考虑在可数背景状态下，时间离散的拟生灭过程(QBD过程)平稳分布的尾概率的渐近态。
The non-stationary signal is widely distributed in the reality, such as audio, radar and sonar signals. Time-frequency analysis is an effective tool to process the non-stationary signals.
非平稳信号广泛存在于很多实际场合中，比如如语音、雷达和声纳中的线性调频信号，时频分析是处理非平稳信号的一个强有力的工具。
EMD method is a new method for analyzing nonlinear and non-stationary data, which has more advantage than wavelet analysis, and it can process short time series precisely.
EMD方法是对非平稳、非线性信号进行分析的一种新的时频分析方法。它比小波分析等方法具有更强的特性并能准确地处理非常短的数据序列。
EMD method is a new method for analyzing nonlinear and non-stationary data, which has more advantage than wavelet analysis, and it can process short time series precisely.
EMD方法是对非平稳、非线性信号进行分析的一种新的时频分析方法。它比小波分析等方法具有更强的特性并能准确地处理非常短的数据序列。
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