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non-stationary random process

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  • Non-homogeneous Poisson process — In probability theory, a non homogeneous Poisson process is a Poisson process with rate parameter λ(t) such that the rate parameter of the process is a function of time.[1] Non homogeneous Poisson process have been shown to describe numerous… …   Wikipedia

  • Stationary process — In the mathematical sciences, a stationary process (or strict(ly) stationary process or strong(ly) stationary process) is a stochastic process whose joint probability distribution does not change when shifted in time or space. Consequently,… …   Wikipedia

  • Point process — In statistics and probability theory, a point process is a type of random process for which any one realisation consists of a set of isolated points either in time or geographical space, or in even more general spaces. For example, the occurrence …   Wikipedia

  • Wiener process — In mathematics, the Wiener process is a continuous time stochastic process named in honor of Norbert Wiener. It is often called Brownian motion, after Robert Brown. It is one of the best known Lévy processes (càdlàg stochastic processes with… …   Wikipedia

  • Convergence of random variables — In probability theory, there exist several different notions of convergence of random variables. The convergence of sequences of random variables to some limit random variable is an important concept in probability theory, and its applications to …   Wikipedia

  • Asymptotic equipartition property — In information theory the asymptotic equipartition property (AEP) is a general property of the output samples of a stochastic source. It is fundamental to the concept of typical set used in theories of compression.Roughly speaking, the theorem… …   Wikipedia

  • Lévy process — In probability theory, a Lévy process, named after the French mathematician Paul Lévy, is any continuous time stochastic process that starts at 0, admits càdlàg modification and has stationary independent increments this phrase will be explained… …   Wikipedia

  • Continuous-time Markov process — In probability theory, a continuous time Markov process is a stochastic process { X(t) : t ≥ 0 } that satisfies the Markov property and takes values from a set called the state space; it is the continuous time version of a Markov chain. The… …   Wikipedia

  • Gibbs sampling — In statistics and in statistical physics, Gibbs sampling or a Gibbs sampler is an algorithm to generate a sequence of samples from the joint probability distribution of two or more random variables. The purpose of such a sequence is to… …   Wikipedia

  • Spectral density — In statistical signal processing and physics, the spectral density, power spectral density (PSD), or energy spectral density (ESD), is a positive real function of a frequency variable associated with a stationary stochastic process, or a… …   Wikipedia

  • Detrended fluctuation analysis — In stochastic processes, chaos theory and time series analysis, detrended fluctuation analysis (DFA) is a method for determining the statistical self affinity of a signal. It is useful for analysing time series that appear to be long memory… …   Wikipedia

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