Signals and Systems

Electronics and communication engineering deals with signal processing and signal transmission. This field of engineering is known as signals and systems. In this article, we will introduce the readers to signals and systems by defining all the necessary ​​terms and discussing the components that make up the communication system.

We will also categorize signals and systems based on their classification and try to understand them through circuit diagrams. The later part of the article will talk about the characteristics, advantages, and applications of signals and systems along with some limitations. The article will conclude with some frequently asked questions that the readers can refer to.

The term signals and systems is a self-explanatory term involving the electronic systems needed for dealing with signals. These systems are equipped with the task of processing, modulating, and transmitting the signal. Let us look at the formal definition of the systems and signals.

Signals and Systems are used for studying the different systems made using electronic circuits which are then used for working with signals that have necessary information.

Let us study the components that make up signals and systems

• Input: As shown in the block diagram above, Input refers to the analog or digital signal that is fed to the system for processing. The final value is obtained by performing operations on the input values.
• System: The system is made of internal circuitry that is designed to perform certain specific operations on the signals like modulation or filtering of signal. The system is used for processing the original input that was sent.
• Output: The output refers to the final signal that is generated after processing the input signal. This signal is then used or transmitted to some channel depending on the need of the signal.

The signal can be represented by mathematical equations depending on whether the signal is periodic or non-periodic. A periodic signal can be easily represented using trigonometric equations or other periodic functions. Here is the mathematical equation for a period signal represented in the figure below.

Here is a representation of the signal.

Y= A sin(x)

Amplitude(A) = 1

period= 3600= 2?

Let us study the classification of signals based on their distribution in the time domain.

• Analog signals: Analog signals are continuous time signals and they are used to represent data over a range of values. These are used to represent analogous values that vary with the continuous value of input for example the audio signals vary continuously with pressure change
• Human voice: This signal is produced by the larynx present in the throat of human beings. The vibration of vocal cords due to the passage of air results in the audio signal. The frequency of human sound is 350 Hz to 17KHz for women and 100Hz to 8KHz for men.
• Digital signals: Contrary to analog signals, digital signals are discrete in nature therefore, they are used to represent values that vary discretely with time. There are discontinuities in the digital signals, some examples of digital signals are signals in smartwatches and phones.

The system is made of internal circuitry that is designed to perform certain specific operations on the signals like modulation or filtering of signal. The system is used for processing the original input that was sent therefore, the system can be understood as a transformation to the input function. Let us look at a diagram representing a system.

Conversion of analog signals to digital signals can be done using one of these methods. You can look here for a detailed understanding.

• Pulse Code Modulation: This is the most generic method used for converting analog signal to digital signal. The method includes sampling the given analog data, quantization of sampled values, and then encoding the data into a form that can be transmitted.
• Delta Modulation: This technique is used since pulse code modulation is a complex method. This technique uses a modulator which uses a comparator and has a delay unit. The demodulator is further used to extract the original signal.
• Adaptive Delta Modulation: This technique is an improvement in the delta modulation technique. The technique manages to change the step size depending on the modulator and the message signal. There is less data loss in this method.

NOTE : You can learn more about modulation and demodulation

There are certain benefits of converting analog signal to digital signal which have been stated below:

• Storing Digital data is easier as compared to analog data since digital data consists of bits of 0s and 1s therefore, by converting the signal we can reduce the memory required.
• Digital impulses are well defined therefore, transmission of digital signals is easier as compared to analog signals.
• Digital signals are well-propagated signals due to a well-defined sampling rate.
• It is easy for electronic circuits to identify noise in digital circuits rather than analog circuits.
• The conversion of analog to digital signal is used in many real-life applications therefore, the conversion is needed.

Let us compare continuous-time and discrete-time systems

Let us study the characteristics of signals and systems

• Causality: Signals and systems can have a causal system where the current output of the system depends on the present and past input values and is independent of future values. Causality is a requirement of some real-world systems.
• Time Invariant: Time Invariant system can be defined as a system where If an input signal is shifted by some period then the response is that the system is also shifted by the same period. This ensures that the system doesn’t change with time.
• Linearity: Linear systems are defined by their property of superposition. It can be understood as the system response of the sum of two inputs is equal to the sum of the output response of individual input values.
• Stability: Stability is necessary to ensure that the system doesn’t grow uncontrollably, therefore stable systems are the ones that generate bounded output for a bounded input.
• Convolution: Convolution is often used for calculating the output of the system by convoluting the input signal with the transfer function of the system.

Let us study the advantages of signals and systems

• The principles of signals and systems are simple and efficient therefore they can be applied easily with basic knowledge of the subject.
• Signals and systems form the basis of all control systems and other specific signal processing units originate from these circuits.
• Signals and systems are diverse tools used for analyzing analog and digital signals. The knowledge is used in different fields like communication, data processing, and consumer electronics.
• Signals and systems processing are used for transferring Digital signals with minimum interference, therefore minimizing the noise produced.
• Signals and systems can ensure data security by transmitting encrypted signals. These signals are then decrypted only for the authenticated user.

Let us study the limitations of signals and systems

• Signal processing can be unpredictable and unreliable due to inherent inconsistencies in the signal and system design.
• As the systems get complicated, the mathematics used also gets difficult with difficult concepts like convolution, Fourier transform and Laplace transform.
• Signals and systems can degrade the quality of signal due to interference of noise and errors corrupting the original signal.
• Methods involved in signals and systems are designed based on certain assumptions that are not true for real-life signals. This can lead to inaccurate results.
• The signals and systems are effective for dealing with Linear systems therefore they can’t be used to deal with the modeling and processing of nonlinear signals.

Let us study the applications of signals and systems

• Signals and systems are taught as a primary course in professional institutions to develop the basics of electronics engineering.
• Signals and systems are used in fields like multimedia processing for efficient transfer of image and video data with minimal loss.
• Sensing methods located in satellites and navigation ships like SONAR, RADARS, and LiDAR work on the principles of signal processing to analyze the received signals.
• Principles of signals and systems are applied in the study of earthquakes I.e. in seismology to study the vibrations that result as a consequence of collision of plates.
• Signals and systems are also used in the telecommunication industry to compress the signal like audio signals therefore efficiently managing the resources available for data transfer.

We have seen that signals and systems form an integral part of electronics and communication. It is necessary to define these terms to establish a basic understanding of the topic. The circuits are installed in various daily life appliances where they are used for signal processing. The advantages of the signals and systems are evident from their use in different applications. Despite the various features offered, there are some limitations of the system that have been discussed in the article. Readers are suggested to go through the frequently asked questions in case of any doubt.

What are energy signals and what is the power of energy signals?

Energy signals are the ones that have a periodic nature and a converging nature which ensure a limited energy of the signal. These signals are bounded and have 0 power.

What is meant by an LTI system in signals and systems?

LTI systems are characterized by their Linear and time Invariant nature. The output of the LTI system is calculated using the convolution of the input signal and transfer function.

How can you convert analog signal to digital signal?

Techniques like sampling and quantization can be used for discretization of analog values which results in digital values. The more the number of values the more accurate the data will be.