Signal processing is a sub-discipline of either mathematics or electrical engineering depending on who you ask. This discipline deals with encoding, extracting, analyzing, or otherwise dealing with data in respect to Signals. A signal can be thought of as a function of time for most purposes. Signals are the inputs and outputs of Systems. A system takes one or more signals as inputs, does something (or nothing) and returns on or more signals as output.

Basic Notation/Terminology

x(t)

- most common placeholder for an example signal, where x is the signal value and t is time

δ(t)

- impulse function, which has a value of zero everywhere excepting t = 0 where δ(t = 0) has a value of ∞

h(t)

- the "impulse response" of a system, which is the output signal of a 1-input-1-output system when the input signal is δ(t)

Discrete/Continuous

Discrete and continuous refer to different kinds of number domains, where discrete has limited precision and continuous does not. In a continuous domain, it is possible to achieve arbitrary precision. The difference between continuous and discrete is like the difference between the set of real number and integers, and these are usually the signal domains that will be used when dealing with continuous and discrete signals respectively. Also of note, even though both the real set and integer set are infinite, the total of an real numbers is a "bigger infinity" than the set of all integers. This fact makes some of the differences between continuous and discrete signal formulas slightly more intuitive.

See related articles:
The Fourier Transform
The Laplace Transform

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