TITLE: THE ADVANTAGES OF DIGITAL COMMUNICATION AND SIGNAL PROCESSING I. INTRODUCTION
Modern technologies such as digital communication and signal processing have give us a lot of improvement in our life with it’s advantages. II. BODY
A. Medical field will be more efficient with the presence of signal processing. 1. History has been made when The Electrical Engineering Faculty of Universiti Teknologi Malaysia (UTM) poneering the digital signal processing to detect a person’s heart status (Zu Ao,2000). 2. The capabilities of a magnetic resonance imaging (MRI) has been improved through the application of digital signal processing (IEEE, 1999). 3. Digital Signal Processing plays a big role in medical field (Ifeachor,1996). B. Military technology such as radar has been improved by the application of Digital Signal Processing (DSP). 1. Complicated system in military technologies such as radar or sonar can be enabled by using multicore DSP (Rivera,2011). 2. The range of potential application of radar or sonar signal processing has been broadened greatly (Carr,1990).

C. Digital communication make communication in military more reliable. 1. For naval military, shipboard application will be more advance by the usage of digital communication (Bhargava,2002). 2. Digital communication also known as digital transmission is worthwhile to search through the noise in a large bandwidth in order to receive few bits per second (Pierce,1968). D. Digital communication makes data transfer or communication faster 1. Processing important matters has been accelerated by the presence of digital communication. 2. Bandwith can be increase by using digital communication with increased number of bits per sample of signal. III. Conclusion

...EEE 311: DigitalSignalProcessing-I
Course Teacher: Dr. Newaz Md. Syfur Rahim
Associated Professor,
Dept of EEE, BUET, Dhaka 1000.
Syllabus: As mentioned in your course calendar
Reference Books:
1. DigitalSignalProcessing: Principles, Algorithms, and Applications – John G. Proakis
2. DigitalSignalProcessing: A Practical Approach – Emmanuel C. Ifeachor
3. Schaum’s Outlines of DigitalSignalProcessing
4. Modern DigitalSignalProcessing – Roberto Cristi
Course Outlines:
This course will cover Chapter 1 through 5 of Proakis’s and Chapter 5 through 7 of Ifeachor’s book.
Signals Systems and SignalProcessing
A signal is a function of one or more independent variables that usually represent time and/ or space. A signal contains some kind of information that can be conveyed, displayed, or manipulated. Examples of signals of particular interests are:
* Speech, which we encounter in telephony, radio, and everyday life.
* Biomedical signals, such as electrocardiogram
* Sound and music, such as reproduced by CD player
* Video and image, which people watch on television
* Radar signals, which are...

...Electronic and Information Engineering EIE413 DigitalSignalProcessing Individual Essay
Multirate DigitalSignalProcessing
Instructor: W.C. Siu By HAN Shilu 07828567D
EIE413 DigitalSignalProcessing
Multirate DigitalSignalProcessing
Abstract
In traditional digitalsignalprocessing system, there is always only one simple sampling rate (that is, the sampling frequency). The output signal has the same sampling rate with the input. In modern digital systems, however, there is an
increasing need to process data at more than one sampling rate. Sometimes the output of the system is required to have a different sampling rate of the input signal. This has lead the development of multirate digitalsignalprocessing, which is a new sub-area in DSP. For example, the sampling rate for an audio CD (compact disc) is 44.1 kHz. If we want to transfer data from the CD to a DAT (digital audio tape) at a sampling rate of 48 kHz, we need to increase the frequency of the data first using a multirate approach. There are two primary options we have in multirate processing. The first is decimation. The sampling rate fs of a given signal x[n]...

...Lab manual for
DigitalSignalProcessing Lab
III B. Tech II Semester
Prepared by
J. Sunil Kumar, P.Saritha & Ch.Sateesh kumar reddy
Department of Electronics & Communication Engineering
Turbomachinery Institute of Technology & Sciences
(Approved by AICTE & Affiliated to JNTUH) Indresam(v), Patancheru(M), Medak(Dist). Pin: 502 319
Date:…………
DSP Lab Manual ………
Turbomachinery Institute of Technology & Sciences
Certificate
This is to certify that Mr. / Ms. ………………………………….. RollNo……………..… of I/II/III/IV B.Tech I / II Semester of …………….……………………..…………branch has completed the laboratory work satisfactorily in …………………..…….……..... Lab for the academic year 20 … to 20 …as prescribed in the curriculum. Place: …………….….
Date: ……………..….
Lab In charge
Head of the Department
Principal
.
1
Turbomachinery Institute of Technology & Sciences, Hyd. 319
Date:………… LIST OF EXPERIMENTS: 1. Generation of Sinusoidal Waveform / Signal 2. To find the DFT / IDFT of given DT Signal
DSP Lab Manual ………
3. To find the frequency response of a given system in transfer function 4. Implementation of FFT of given sequence 5. Implementation of LP FIR filter for given sequence 6. Implementation of HP FIR filter for given sequence 7. Implementation of LP IIR filter for given sequence 8. Implementation of HP IIR filter for given sequence 9. Determination of power spectrum of...

...DIGITALSIGNAL – IMAGE SIGNALPROCESSING LAB MANUAL
PREPARED BY: B.C.SURVE/SHARATH B.
ASSISTANT PROFESSOR
CONTENTS:
1)Experiment 1: INTRODUCTION WITH MATLAB SOFTWARE
2) Experiment 2: GENERATION OF BASIC CONTINUES SIGNALS / BASIC DISCRETE SIGNALS
3) Experiment 3: IMPULSE RESPONSE OF AN LTI SYSTEM
4) Experiment 4: CONVOLUTION OF TWO SEQUENCE AND PROPERTIES OF CONVOLUTION
5) Experiment 5: CORRELATION- AUTOCORRELATION
6) Experiment 6: read and display digital image using MATLAB
7) Experiment 7: remove noise using spatial filters.
8) Experiment 8: edge detection using quick mask.
9) Experiment 9: histogram calculation and equalization.
(Without using standard functions)
10) Experiment 10: image morphological operations erosion and dilation.
Experiment No: - 01
FAMILIARISATION WITH MATLAB R2011B
Aim: To familiarise with MATLAB software, general functions and signalprocessing toolbox functions.
The name MATLAB stands for Matrix Laboratory produced by Math works Inc., USA. It is a matrix-based
powerful software package for scientific and engineering computation and visualization. Complex numerical problems can be solved in a fraction of the time that required with other high level...

...DSP NOTES PREPARED
BY
nikhil teja
DIGITALSIGNALPROCESSING A signal is defined as any physical quantity that varies with time, space or another independent variable. A system is defined as a physical device that performs an operation on a signal. System is characterized by the type of operation that performs on the signal. Such operations are referred to as signalprocessing. Advantages of DSP 1. A digital programmable system allows flexibility in reconfiguring the digitalsignalprocessing operations by changing the program. In analog redesign of hardware is required. 2. In digital accuracy depends on word length, floating Vs fixed point arithmetic etc. In analog depends on components. 3. Can be stored on disk. 4. It is very difficult to perform precise mathematical operations on signals in analog form but these operations can be routinely implemented on a digital computer using software. 5. Cheaper to implement. 6. Small size. 7. Several filters need several boards in analog, whereas in digital same DSP processor is used for many filters. Disadvantages of DSP 1. When analog signal is changing very fast, it is difficult to convert digital form .(beyond 100KHz range) 2. w=1/2 Sampling rate....

...Mobile communications and digitalsignalprocessing.
Introduction to mobile radio communications.
Spread spectrum.
Modulation techniques.
Introduction.
Mobile communication has seen an unprecedented increase in the number of users over the past years. Its success in part is due to the various technologies that have been developed. It is not unlike other stationary communication systems in many respects however it does differ in others, one obvious one being the environment the signal and data propagate over.
The generic mobile communication system.
Basically this is a transmitter and a receiver see figure Generic mobile communication. There are many varied and complex techniques associated with such a system the figure serves as a basic introduction. As the signal is communicating over spatial (unguided media) it may encounter obstacles.
[pic]
Figure. Generic mobile communication.
Spread spectrum techniques.
A number of techniques are used in mobile communications that are described as spread spectrum techniques, named because they increase the bandwidth required. This effectively increases the bit rate of the signal and gives the signal a unique characteristic.
• Example the data to be transmitted say a '1' is purposely increased in...

...GUJARAT TECHNOLOGICAL UNIVERSITY
Electronics Engineering / Electronics & Communication Engineering /Electronics & Telecommunication Engineering B. E. SEMESTER: VII
Subject Name: DigitalSignalProcessing Subject Code: 171003 Teaching Scheme
Theory Tutorial Practical Total
Evaluation Scheme
University Exam (E) Theory Practical 70 30 Mid Sem Exam (Theory) (M) 30 Practical (Internal)
4
0
2
6
20
Sr. Course Content No 1. Introduction: Signals, systems and signalprocessing, classification of signals, elements of digitalsignalprocessing system, concept of frequency in continuous and discrete time signals, Periodic Sampling, Frequency domain representation of sampling, Reconstructions of band limited signals from its samples, general applications of DSP 2. Discrete-Time Signals and Systems: Discrete-Time Signals, Discrete-Time Systems, LTI Systems, Properties of LTI Systems, linear convolution and its properties, Linear Constant Coefficient Difference equations,. Frequency domain representation of Discrete-Time Signals & Systems, Representation of sequences by discrete time Fourier Transform, (DTFT), Properties of discrete time Fourier Transform, and correlation of signals, Fourier Transform Theorems. 3. The Z-...

...Lab 1: Sampling Theory, Quantization and PCM
In this lab, you will familiar with Sampling theorem, quantization and PCM generation. Pre-lab Assignment
: Given signal
x(t) = sinc(t), x(t).
1. Find out the Fourier transform of
x(t), X(f ), sketch them;
2. Find out the Nyquist sampling frequency of 3. Given sampling rate terms of
fs , write down the expression of the Fourier transform of xs (t) → Xs (f ) in fs = 1
Hz, sketch the sampled signal
X(f ). xs (t) = x(kTs )
and the Fourier
4. Let sampling frequency transform of
xs (t). fs = 2Hz , repeat 4. fs = 0.5Hz , repeat 4. fs = 1.5Hz , repeat 4. fs = 2/3Hz , repeat 4.
5. Let sampling frequency 6. Let sampling frequency 7. Let sampling frequency 8. Let sampling frequency
Lab Assignment 1: Sampling Theorem 1. Design matlab programs to illustrate items 3-8 in pre-lab assignment. You need to plot all the graphs. Using the Fourier transform of
xs (t) as: x(kTs ) exp(−j 2πf kTs )
k
Xs (f ) =
2. Compare your results with your sketches in your pre-lab assignment and explain them.
Lab Assignment 2: Quantization of Voice 1. Read pcm.wav le into vector
y (you can truncate the original data to the desired length); N = 3
bits (8 levels) uniform quantizer. Output PCM code
2. Quantize the data vector N number (0 to 2 − 1).
y,
using
3. Generate binary (0 and 1) bit stream from PCM code number (this bit stream will be used in the later labs). 4....

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