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Once the message has been sent, becomes the process , while () becomes the process [/], which is with the place-holder substituted by , the data received on . The class of processes that P {\displaystyle {\mathit {P}}} is allowed to range over as the continuation of the output operation substantially influences the properties of the calculus.
For a non-holonomic process function, no such function may be defined. In other words, for a holonomic process function, λ may be defined such that dY = λδX is an exact differential. For example, thermodynamic work is a holonomic process function since the integrating factor λ = 1 / p (where p is pressure) will yield exact ...
The definition of this function defines the possible interactions between processes — those pairs of actions that do not constitute interactions are mapped to the deadlock action, , while permitted interaction pairs are mapped to corresponding single actions representing the occurrence of an interaction. For example, the communications ...
While a computer program is a passive collection of instructions typically stored in a file on disk, a process is the execution of those instructions after being loaded from the disk into memory. Several processes may be associated with the same program; for example, opening up several instances of the same program often results in more than ...
Flowchart of using successive subtractions to find the greatest common divisor of number r and s. In mathematics and computer science, an algorithm (/ ˈ æ l ɡ ə r ɪ ð əm / ⓘ) is a finite sequence of mathematically rigorous instructions, typically used to solve a class of specific problems or to perform a computation. [1]
In computer science, a deterministic algorithm is an algorithm that, given a particular input, will always produce the same output, with the underlying machine always passing through the same sequence of states. Deterministic algorithms are by far the most studied and familiar kind of algorithm, as well as one of the most practical, since they ...
The transfer function for a first-order process with dead time is = + (), where k p is the process gain, τ p is the time constant, θ is the dead time, and u(s) is a step change input. Converting this transfer function to the time domain results in
If f(t) is a non-decreasing scalar function of t, then Z(t) = X(f(t)) is also a Gauss–Markov process If the process is non-degenerate and mean-square continuous, then there exists a non-zero scalar function h ( t ) and a strictly increasing scalar function f ( t ) such that X ( t ) = h ( t ) W ( f ( t )), where W ( t ) is the standard Wiener ...