Sources produce signals without having input. We like to think of these as having controllable parameters, like amplitude and frequency. Examples would be oscillators that produce periodic signals like sinusoids and square waves and noise generators that yield signals with erratic waveforms (more about noise subsequently). Simply writing an expression for the signals they produce specifies sources. A sine wave generator might be specified by y⁢t=A⁢sin2⁢π⁢ f 0 ⁢t⁢u⁢t y t A 2 f 0 t u t , which says that the source was turned on at t=0 t 0 to produce a sinusoid of amplitude AA and frequency f 0 f 0 .

An amplifier multiplies its input by a constant known as the amplifier gain.

Figure 1: An amplifier.

amplifier

The gain can be positive or negative (if negative, we would say that the amplifier inverts its input) and its magnitude can be greater than one or less than one. If less than one, the amplifier actually attenuates. A real-world example of an amplifier is your home stereo. You control the gain by turning the volume control.

A system serves as a time delay when the output signal equals the input signal at an earlier time.

Figure 2: A delay.

delay

Here, τ τ is the delay. The way to understand this system is to focus on the time origin: The output at time t=τ t τ equals the input at time t=0 t 0 . Thus, if the delay is positive, the output emerges later than the input, and plotting the output amounts to shifting the input plot to the right. The delay can be negative, in which case we say the system advances its input. Such systems are difficult to build (they would have to produce signal values derived from what the input will be), but we will have occasion to advance signals in time.

Here, the output signal equals the input signal flipped about the time origin.

Figure 3: A time reversal system.

time reversal

Again, such systems are difficult to build, but the notion of time reversal occurs frequently in communications systems.

Systems that perform calculus-like operations on their inputs can produce waveforms significantly different than present in the input. Derivative systems operate in a straightforward way: A first-derivative system would have the input-output relationship y⁢t=dd t x⁢t y t t x t . Integral systems have the complication that the integral's limits must be defined. It is a signal theory convention that the elementary integral operation have a lower limit of −∞ , and that the value of all signals at t=−∞ t equals zero. A simple integrator would have input-output relation

Linear systems are a class of systems rather than having a specific input-output relation. Linear systems form the foundation of system theory, and are the most important class of systems in communications. They have the property that when the input is expressed as a weighted sum of component signals, the output equals the same weighted sum of the outputs produced by each component. When S⁢· S · is linear,

This general input-output relation property can be manipulated to indicate specific properties shared by all linear systems.

We can find the output of any linear system to a complicated input by decomposing the input into simple signals. The equation above says that when a system is linear, its output to a decomposed input is the sum of outputs to each input. For example, if x⁢t=e−t+sin2⁢π⁢ f 0 ⁢t x t t 2 f 0 t the output S⁢x⁢t S x t of any linear system equals y⁢t=S⁢e−t+S⁢sin2⁢π⁢ f 0 ⁢t y t S t S 2 f 0 t

Systems that don't change their input-output relation with time are said to be time-invariant. The mathematical way of stating this property is to use the signal delay concept described in Simple Systems.

The collection of linear, time-invariant systems are the most thoroughly understood systems. Much of the signal processing and system theory discussed here concentrates on such systems. For example, electric circuits are, for the most part, linear and time-invariant. Nonlinear ones abound, but characterizing them so that you can predict their behavior for any input remains an unsolved problem.