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An information processor or information processing system, as its name suggests, is a system (be it electrical, mechanical or biological) which takes information (a sequence of enumerated symbols or states) in one form and processes (transforms) it into another form, e.g. to statistics, by an algorithmic process.
An information processing system is made up of four basic parts, or sub-systems:
An object may be considered an information processor if it receives information from another object and in some manner changes the information before transmitting it. This broadly defined term can be used to describe every change which occurs in the universe. As an example, a falling rock could be considered an information processor due to the following observable facts:
First, information in the form of gravitational force from the earth serves as input to the system we call a rock. At a particular instant the rock is a specific distance from the surface of the earth traveling at a specific speed. Both the current distance and speed properties are also forms of information which for that instant only may be considered "stored" in the rock.
In the next instant, the distance of the rock from the earth has changed due to its motion under the influence of the Earth's gravity. Any time the properties of an object change a process has occurred meaning that a processor of some kind is at work. In addition, the rock's new position and increased speed is observed by us as it falls. These changing properties of the rock are its "output."
In this example, both the rock and the earth are information processing systems, because both objects change the properties of the other over time.
If change occurs, information is processed.
Information theory approach
From the stance of information theory, information is taken as a sequence of symbols from an alphabet, say an input alphabet χ, and an output alphabet ϒ. Information processing consists of an input-output function that maps any input sequence from χ into an output sequence from ϒ. The mapping may be probabilistic or determinate. It may have memory or be memoryless.
- Stephen B. Wicker, Saejoon Kim (2003). Fundamentals of Codes, Graphs, and Iterative Decoding. Springer. pp. 1 ff. ISBN 1402072643.