Properties of Signals
A signal can be classified as periodic or aperiodic; discrete or continuous time; discrete of continuous-valued; or as a power or energy signal. The following defines each of these terms. In addition, the signal-to-noise ratio of a signal corrupted by noise is defined.
Periodic / Aperiodic:
A periodic signal repeats itself at regular intervals. In general, any signal x(t) for which for all t is said to be periodic.
The fundamental period of the signal is the minimum positive, non-zero value of T for which above equation is satisfied. If a signal is not periodic, then it is aperiodic.
Symmetric / Asymmetric:
There are two types of signal symmetry: odd and even. A signal x(t) has odd symmetry if and only if x(-t) = -x(t) for all t. It has even symmetry if and only if x(-t) = x(t).
Continuous and Discrete Signals and Systems
A continuous signal is a mathematical function of an independent variable, which represents a set of real numbers. It is required that signals are uniquely defined in except for a finite number of points.
Example: A rectangular wave is discontinuous at several points but it is continuous time signal.
Discrete / Continuous-Time Signals:
A continuous time signal is defined for all values of t. A discrete time signal is only defined for discrete values of t = ..., t-1, t0, t1, ..., tn, tn+1, tn+2, ... It is uncommon for the spacing between tn and tn+1 to change with n. The spacing is most often some constant value referred to as the sampling rate,
Ts = tn+1 - tn.
It is convenient to express discrete time signals as x(nTs)= x[n].
That is, if x(t) is a continuous-time signal, then x[n] can be considered as the nth sample of x(t).
Sampling of a continuous-time signal x(t) to yield the discrete-time signal x[n] is an important step in the process of digitizing a signal.
Energy and Power Signal:
When the strength of a signal is measured, it is usually the signal power or signal energy that is of interest.
The signal power of x(t) is defined as
and the signal energy as
Signal to Noise Ratio:
Any measurement of a signal necessarily contains some random noise in addition to the signal. In the case of additive noise, the measurement is
x(t) = s(t)+n(t)
where s(t) is the signal component and n(t) is the noise component.
The signal to noise ratio is defined as
or in decibels,
The signal to noise ratio is an indication of how much noise is contained in a measurement.
Standard Continuous Time Signals
where ∞ is the hight of impulse signal havig unit area.
and When A = 1 (unit impulse Area)
Where, Angular frequency in red/sec
f0 = frequency in cycle/sec or Hz
T = time period in second
Classification of Continuous Time Signal: The continuous time signal can be classified as
1. Deterministic and Non-deterministic Signals:
2. Symmetric (even) and Anti-symmetric (odd) Signals
When a signal exhibits symmetry with respect to t = 0, then it is called an even signal.
x(-t) = x(t)
When a signal exhibits anti-symmetry with respect to t = 0, then it is called an odd signal.
x(-t) = -x(t)
Let X(t) = Xe(t) + X0(t)
Where, Xe(t) = even part of X(t)
X0(t) = odd part of X(t)
The discrete signal is a function of a discrete independent variable. In a discrete time signal, the value of discrete time signal and the independent variable time are discrete. The digital signal is same as discrete signal except that the magnitude of the signal is quantized. Basically, discrete time signals can be obtained by sampling a continuous-time signal. It is denoted as x(n).
Standard Discrete Time Signals