Random Process
A —- generates outcomes that are determined purely by chance.
A random process is a mathematical model that describes how the values of a particular quantity change over time, where these values are determined by chance or probability. Also known as a stochastic process, it is a sequence of random variables that evolve over time and can be used to model and analyze diverse random phenomena. Random processes are essential in many fields of science and engineering, including signal processing, communication systems, finance, biology, and physics.
A random process can be classified as either discrete-time or continuous-time, depending on the values of the random variables and the timing of their occurrence. In a discrete-time random process, the random variables take on values at discrete intervals, whereas in a continuous-time random process, the random variables change continuously over time.
There are different types of random processes, including stationary and non-stationary random processes. A stationary random process is one whose statistical properties remain constant over time, while a non-stationary random process has statistical properties that vary with time. Also, there are various tools and techniques used to analyze random processes, such as probability distributions, correlation functions, power spectral density, and Markov models.
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