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Stochastic Process

Creator
Creator
Seonglae Cho
Created
Created
2023 Jul 11 17:18
Editor
Editor
Seonglae Cho
Edited
Edited
2024 Dec 28 14:26
Refs
Refs
Sequential Data
확률 과정은 시간의 진행에 대해 확률적인 변화를 가지는 구조를 의미
Stochastic Processes
Gaussian Process
Markov Model
Wiener Process
Stationary process
 
 
 
Stochastic Process Notion
Random Walk
Ergodicity
Stochastic matrix
Stationary distribution
Sample Path
 
 
 
 
Stochastic process
In probability theory and related fields, a stochastic or random process is a mathematical object usually defined as a sequence of random variables, where the index of the sequence has the interpretation of time. Stochastic processes are widely used as mathematical models of systems and phenomena that appear to vary in a random manner. Examples include the growth of a bacterial population, an electrical current fluctuating due to thermal noise, or the movement of a gas molecule. Stochastic processes have applications in many disciplines such as biology, chemistry, ecology, neuroscience, physics, image processing, signal processing, control theory, information theory, computer science, and telecommunications. Furthermore, seemingly random changes in financial markets have motivated the extensive use of stochastic processes in finance.
Stochastic process
https://en.wikipedia.org/wiki/Stochastic_process
Stochastic process
 
 

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Stochastic Process
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