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A Dirac comb is an infinite series of Dirac delta functions spaced at intervals of T. A so-called uniform "pulse train" of Dirac delta measures, which is known as a Dirac comb, or as the Sha distribution, creates a sampling function, often used in digital signal processing (DSP) and discrete time signal analysis
The Dirac measures are the extreme points of the convex set of probability measures on X. The name is a back-formation from the Dirac delta function; considered as a Schwartz distribution, for example on the real line, measures can be taken to be a special kind of distribution. The identity
The delta potential is the potential = (), where δ(x) is the Dirac delta function. It is called a delta potential well if λ is negative, and a delta potential barrier if λ is positive. The delta has been defined to occur at the origin for simplicity; a shift in the delta function's argument does not change any of the following results.
The Dirac measure is a discrete measure whose support is the point 0. The Dirac measure of any set containing 0 is 1, and the measure of any set not containing 0 is 0. In mathematics , more precisely in measure theory , a measure on the real line is called a discrete measure (in respect to the Lebesgue measure ) if it is concentrated on an at ...
For example, the Dirac delta function is a singular measure. Example. A discrete measure. The Heaviside step function on the real line, = {, <;,; has the Dirac delta distribution as its distributional derivative.
The impulse can be modeled as a Dirac delta function for continuous-time systems, or as the discrete unit sample function for discrete-time systems. The Dirac delta represents the limiting case of a pulse made very short in time while maintaining its area or integral (thus giving an infinitely high peak). While this is impossible in any real ...
During the late 1920s and 1930s further basic steps were taken. The Dirac delta function was boldly defined by Paul Dirac (an aspect of his scientific formalism); this was to treat measures, thought of as densities (such as charge density) like genuine functions.
Examples of the latter include the Dirac delta function and distributions defined to act by integration of test functions against certain measures on . Nonetheless, it is still always possible to reduce any arbitrary distribution down to a simpler family of related distributions that do arise via such actions of integration.