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一个用于解决马尔可夫过程的源代码,很适合学习随机过程的同学1-a Markov process for the settlement of the source code, are very suitable for studying stochastic process a classmate
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Measuring Frequency Content in
Signals
I this section we will study some non parametric methods for spectrum estimation
of a stochastic process. These methods are described in the literature.
All methods are based on the Periodogram which is
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This program calibrates the Ornstein–Uhlenbeck process, a mean reverting AR(1) stochastic process. The parameters are estimated using (1)Least Squares fitting and (2)Maximum Likelihood estimation.-This program calibrates the Ornstein–Uhlenbeck proces
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在离散时间随机过程中,通过卡尔曼滤波计算公式估计求观测信号的系数-In the discrete-time stochastic process, the formula is estimated by Kalman filter coefficients observed signal demand
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分别用非参数化谱估计中的直接法,间接法和加窗法对离散随机过程的已零均值化的N个数据样本估计了离散信号的谱密度。-Were non-parametric spectral estimation of the direct method, indirect method and windowing method, discrete stochastic process has zero mean the data of the N-sample estimates of the spectral d
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In probability theory, a stochastic process, or sometimes random process, is the counterpart to a deterministic process (or deterministic system). Instead of dealing with only one possible reality of how the process might evolve under time (as is the
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随机过程ppt课件 华中科技大学 刘次华-the ppt of stochastic process by liucihua of Huazhong University of Science & Technology
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随机过程在三国杀中的数学建模及matlab仿真报告-Three killed in Stochastic Process in Mathematical Modeling and Simulation Report matlab
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随机过程,描述时间序列、马尔科夫链等经典随机过程问题的好书-stochastic process
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遗传算法的描述。遗传算法是一种很经典的随机化过程的算法,在实际应用中应用广泛,效果良好。-A descr iption of the genetic algorithm. The genetic algorithm is a classical stochastic process of the algorithm, widely used in practical applications to good effect.
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随机过程的重要公式,希望对大家有用,自己总结的,请使用-Random process formula, we want to
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随机过程: ,其中 是均值为零、方差为1的白噪声, 、 是相互独立并在 上服从均匀分布的随机相位。采用AIC和MDL准则估计信号源个数,并且画出相应的MUSIC频率估计谱线。
要求:信号样本数为1000,估计的自相关矩阵为8阶。
-Stochastic process: where is zero mean and variance 1 white noise, are independent and uniformly distributed on a random phase. Es
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马尔可夫链,因安德烈·马尔可夫(A.A.Markov,1856-1922)得名,是数学中具有马尔可夫性质的离散时间随机过程。该过程中,在给定当前知识或信息的情况下,过去(即当期以前的历史状态)对于预测将来(即当期以后的未来状态)是无关的-Markov chain, Yinandelie · Markov (AAMarkov ,1856-1922) got its name, is a discrete time stochastic process with Markov mathematica
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理解掌握
Poisson过程的理论,了解随机过程的模拟实现技术,学习并掌握在实际中如何检验给定的随机过程是否为Poisson过程
-Poisson process, understand and grasp the theory of stochastic processes to achieve understanding of simulation techniques to learn and master in practice how to verify whether a g
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yacine随机过程估计代码matlab的实现和应用-Stochastic Process Matlab
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随机过程基础课程,包含泊松过程、马尔可夫链、鞅等经典方法,清晰详细,有案例讲解-Stochastic Processes basic courses, including Poisson process, Markov chain, martingale and other classical methods, clear and detailed, there is case to explain
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随机过程,随机白噪声的产生。小例子。仅供学习参考。-Stochastic process, random white noise. Small example. Only to learn reference.
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随机产生,并服从正态分布。随机过程课本练习实例。-Stochastic process, random white noise. Small example. Only to learn reference.
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stochastic process of the stochastic resonance
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隐Markov模型(简称为HMM)是在Markov模型的基础上发展而来的。由于实际问题比Markov模型所描述的问题更为复杂,观测到事件并不是与状态一一对应,而是通过一组观测概率分布相联系,这样的模型称为HMM。它是一个双重随机过程,其中之一是Markov链,这是一个基本的随机过程,描述状态之间的转移。另一个随机过程描述状态和观测变量之间的统计对应关系,这样,站在观察者的角度,只能看到观察值,不象Markov模型中的观测值和状态一一对应。(The implicit Markov model (H
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