Course contents and signal types  | EE MSP 01| Electrical Engineering Education
Channel: Electrical Engineering Education
Date: 11/11/2020

“A signal, is a physical quantity, or quality, which conveys information”. Signals, can take many forms. Examples of signals, include light, sound, radio transmissions, and obviously electrical signals in circuits. In this video presentation, we examine some basic signal types, and define some of the fundamental properties of systems capable of processing/modifying those signals. A signal, can be defined most generally, as a function, f(x), where, ‘x’ can be ‘real’ or ‘imaginary’, and in theory, can represent any quantity, such as position, pressure or temperature. But most often, a signal is defined in terms of ‘real time’, t. Thus, in most of the discussions in these presentations, the signal will be defined in terms of time, f(t). It should, however, be simple to generalize the techniques, so that they can be applied to other forms of ‘x’.  There are three basic types of signals, including, analog, discrete and digital signals.

An analog signal is defined for all values of the continuous variable, t. It’s amplitude can assume any value of a continuous range. Some property of the medium is used to convey the signal's information. For example, an aneroid barometer uses rotary position as the signal to convey pressure information. In an electrical system, the voltage, current, or frequency (or phase) of the signal may be varied to represent the information. 
Examples of analog signals are shown. Both are time varying, having, minimum and maximum values, which can be either, positive or negative. The signals can be periodic, such as sinusoidal signal on the right. On the left a decaying exponential signal is shown. Note that, A bipolar square wave is an analog signal as it’s minimum value is negative. Random signals such as audio and video, are examples of analog signals as well.
 A Discrete-Time Signal only has amplitude values defined for discrete values of time, t. Thus, t usually assumes discrete values, that are integral multiples of some basic quantity, T. For example, f of (t ) is equal to f of (‘n’, T) where n = 0,±1,±2,K. 
A Digital Signal, is like a discrete-time signal, in that, both types of signal are defined for discrete values, of time. The difference is that, a digital signal’s amplitude may only assume discrete values, that are multiples of the same, quantity. This kind of signal is suitable for manipulation by computers, and is therefore, in common use in many applications.
A general example of digital signals is shown. Digital signals are commonly referred to as square waves or clock type of signals. Their minimum value must be 0 volts, and their maximum value must be, for example, ‘A’ volts. They can be periodic, (repeating) or non-periodic. The time the signal is high can vary anywhere from 1% of the period to 99% of the period, which is the duty cycle. Text and Integers, are among the examples of digital signals. Note that analog signals have more exact values, however, are more difficult to work with while realizing the benefits of digital signals such as storage, security, compression, and many other features. 
In Real time signal processing, x of (n) is defined as the input signal representing the sampled value every ‘T’ x. y(n) is output signal representation sampled every ‘T’, y. Signal processing is a transformation F of input samples x(n) to obtain the output signal y(m)=F(x(n)). Tc is a computation time needed to process L input samples. System that has Tc ≤ L ‘T’, x is said to operate in real-time. Conditions for real-time processing are, (1), the input sample period Tx, (2), the complexity of the transformation F, (3), the speed of the signal processing computer which compute F of (x of (n)) as measured by ‘T’,c.  computations with one input sample, that is, sample by sample, are completed before the next input sample arrives. In Block processing, each input sample, x of (n) is stored in memory before any processing occurs upon it. After ‘L’, input samples have arrived, the entire collection of samples is processed at once. In Vector processing , systems with several input and/or output signals being computed at once: this can work with streams or blocks. The DSP algorithms are designed and analysed in Matlab, converted into C or C++ and are implemented in a Digital signal processor or computer, the process data is either shared to another computer or Digital to analog converter for the desired playback. 
We will be using Electrical signals in circuits, since the many real world systems can be represented by electrical circuit equivalents. For example, Acoustic fields, automotive suspension systems. Learning analysis techniques for circuits, helps one to analyse many other types of system, as in general the system is characterized by a differential equation or set of equations that relate the inputs and outputs of the system. Hopefully, you will enjoy learning the course. If you are happy with the contents, please subscribe for future notifications.