Discrete-Time Process
Jump to navigation
Jump to search
A Discrete-Time Process is a process whose events occur on discrete time intervals.
- Context:
- It can (often) be modeled by a Discrete-Time Model (a random variable sequence that ...).
- It can range from being a Discrete-State Discrete-Time Process to being a Continuous-State Discrete-Time Process.
- It can range from being a Fully-Observable Discrete-Time Process to being a Partially-Observable Discrete-Time Process.
- It can range from being a First-Order Discrete-Time Process to being a Higher-Order Discrete-Time Process.
- It can range from being a Stochastic Discrete-Time Process to being a Deterministic Discrete-Time Process.
- …
- Example(s):
- A Deterministic Discrete-Time Process, such as:
- The number sequence generated by the Fibonacci series (can be modeled as F(n) = F(n-1) + F(n-2), where F(n) is the nth number in the sequence, and F(0)=0, F(1)=1).
- The output of a machine that produces a constant number of parts per hour, given a stable input and settings.
- …
- A Stochastic Discrete-Time Process, such as:
- The number of cars that pass through an intersection in a given hour (can be modeled with random variables: X(0), X(1), X(2), ..., where X(n) is the number of cars that pass through the intersection in the nth hour).
- …
- A Deterministic Discrete-Time Process, such as:
- Counter-Example(s):
- See: Temporal Bayesian Model, Markov Decision Process, Continuous-Time Process.
References
2023
- GBard
- A discrete-time process is a sequence of random variables, where each random variable represents the value of the process at a specific point in time. The time intervals between the successive points in time are typically equal, but they do not have to be.
Discrete-time processes are used in many different fields, including engineering, science, and economics. Some examples of discrete-time processes include:
The number of customers arriving at a store in a given hour. The stock market prices of a particular company at the end of each trading day. The temperature readings from a weather station every minute. The audio signal from a digital recording.
Discrete-time processes can be analyzed using a variety of mathematical tools, including probability theory, statistics, and signal processing.
Time intervals: The time intervals between successive hours, which are equal to one hour in this case.