ME606 Digital Signal Processing Assignments Solution

ME606 Digital Signal Processing Assignments Solution

ME606 Digital Signal Processing Assignments Solution

Introduction

A signal generally is a refers to a formal description of a phenomena evolving over space and time. Signal processing refers to any mechanical or manual operational management which analyzes, manipulates or otherwise modifies the data contained in a signal[ CITATION Mar13 \l 1033 ]. Conceptually it is very essential to know that signal processing operates on an abstract representation of a physical quantity and not he quantity itself. The field of signal processing in communication has grown at an alarming rate due to the affordability and availability of digital computers in implementing signal processing algorithms. The signal processing in communication has broadened into the application of various technologies both analog and digital. The earliest ever recorded example for digital processing dates back to 25th century BC.

1960s is well known as the uprising year for the Digital signal processing as it led to development of space exploration, sonar and radar. Signal processing has been used for implementations in many other fields which uses it and have developed technology with their specialized techniques, specific algorithms and their arithmetic[ CITATION Tad13 \l 1033 ]. The Digital signal processing enhances the reliability and accuracy in the field of digital communication. Normally digital signal processing first converts an analog signal into a digital signal and then be relevant signal processing technique and algorithms, at the same time it helps to reduce distortion and noise. The fundamental of digital signal processing is that it works by standardizing the levels of a given signal. All the communication channels have some background noise whether the signals are digital or analog, and apart from which type of data is being transferred. This noise in reference to some signal is referred to as signal to noise ratio for communication systems, usually one tries to determine how it enhances. Suppose an incoming analog signal like that of a television broadcast station, the signal is usually converted to digital fist by use of analog-to-digital converter and the resulting digital signal has either two or more levels., usually this levels are knowable. Because the incoming analog signal contains noise hence many times the levels are not at typical values., with that the digital signal processing correct the values of levels and remove the noise. And he resulting digital signal is changed back o analog by using the digital-to-analog converter[ CITATION Har16 \l 1033 ]. The block diagram below shows the digital signal processing system.

Fig 1: the digital signal processing system

Signals and Systems

The accepted scientific definations of a signal is ‘the physical quantity that changes with time and space and other independent variables. The electroencephalogram (EEG) and electrocardiogram (ECG) are good examples of natural signals. A signal can be either digital or analog. The analog signals have infinite number of values in range while on the other hand the digital waves have only a finite number of values[ CITATION Rob11 \l 1033 ]. Normally in communication there is either usage of periodic analog or aperiodic digital signal. The moment a human being speaks there is a wave generated and the wave is analog. when the wave is captured by a microphone then it is converted to an analog signal and when it is stored in a computer it becomes a digital signal.

Fig 2: classification of speech signals

Digital Speech processing

Speech is the main communication medium and it can be characterized in terms of signals and usually signals contain very important information and the contained information I in acoustic waveform. Speech signal involves application of signal processing method. For the purpose of speech, a signal play three roles. i.e. it represents a speech signal in digital form, classes of application and the implementation of complex techniques. In order to represent a speech in digital form, sampling theorem is used in case of sampling[ CITATION Pao16 \l 1033 ].

Advantages and disadvantages of SIGNAL PROCESSING SYSTEM

The most appropriate reason of using the digital processing methods is that the highly advanced signal processing functions are able to be implemented by use of the signal processing techniques. The digital signal processing is complex in nature than the analog signal processing on the other side the digital signal processing has many advantages as compared to the analog signal processing. Below are some of the advantages of the digital signal processing.

Digital signal processing offers the facility of reproducibly, that is the business system permits the reconfiguration of the digital signal processing functions on the other hand the analog signal processing redesigns the hardware.

The digital signal processing has the ability to be changed this is because the digital processing can be converted or changed any time by programming.

Application of signal processing in communication.

There are many applications in various areas within the field of communication where the signal processing becomes the final solution and due to that signal processing makes available the most promising combination of performances. Some 0f the notable examples where the signal processing has widely been used in communication include;

Speech recognition this includes the speaker verification, speech synthesis and voice mails.

Signal analysis, the signal processing plays a very important role in analyzing signals for instance in analysis of audios and videos this process pays a very important role.

Waveform generation, waveform is used to represent speeches in various fields, with that the signal processing has been used to aid in representing various types of speeches[ CITATION Mar14 \l 1033 ].

Signal processing is used in filtering the background noise; this is aimed at removing the white noise from a signal/speech.

The signal processing plays a very crucial role in the expansion and compression of speech is used in the radio voice communication.

The design and construction of the radar and sonar system greatly relies on the signal processing. The radar plays a very essential role in radio frequency and secure spread spectrum radios.

In data communication and telecommunication, signal processing plays a very important role that is achieved by the use of pulse modulation system.

In communication images are known to play a crucial role and with the application of signal processing, it is much easier to carry out image processing, that is achieved by image enhancement, image compression and 3D amination and rotation of the images.

Sampling of a signal

Sampling refers to the process of changing a continues time signal into a discrete time signal by taking sample of the continues time signal at discrete time intervals. The rate of sampling can be defined by number of samples that are obtained per second from the analog signal to build a discrete signal. Sampling interval is obtained from the inverse of the sampling frequency or it can be obtained by determining the time difference between successive samples. The SI unit of sampling rate is hertz[ CITATION Gor12 \l 1033 ].

Conclusion

In conclusion, the idea of signal processing is an integrated circuit which is well designed for the purpose of handling high speed data, also it is a technique of examining and modifying a signal in order to enhance its effectiveness. A signal can be either digital or analog. The analog signals have infinite number of values in range while on the other hand the digital waves have only a finite number of values. The processing involves use of various computational and mathematical algorithms to generate a signal which is of higher value than the original signal. Continuous and fast developments in the field of signal processing methods, offers procedures in many areas in reference to the analog signal processing. In the recent past digital signal processing has been used in many signal analyses such as biomedical signal processing, speech signal processing, geophysical signal processing and telecommunications.

There is wide applications of the signal processing in communication such as; Speech recognition, Waveform generation, filtering the background noise and it plays a very crucial role in the expansion and compression of speech is used in the radio voice communication.

References

1. M. Frerking, Digital Signal Processing in Communications Systems, Chicago: Springer Science & Business Media, 2013.
2. T. Wysocki, Digital Signal Processing for Communication Systems, Texas: Springer Science & Business Media, 2013.
3. Harris, Multirate Signal Processing For Communication Systems, London: Pearson Education, 2016.
4. R. Istepanian, Underwater Acoustic Digital Signal Processing and Communication Skill Systems, Chicago: Springer Science & Business Media, 2011.
5. P. Prandoni, Signal Processing for Communications, London: Collection le savoir suisse, 2016.
6. M. Eisencraft, Chaotic Signals in Digital Communications, Texas: CRC Press,, 2014.
7. G. J. Frazer, Application of Digital Signal Processing to Communication Systems in the Electricity Industry, Sydney: University of Queensland, 2012.