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Introduction to Digital signal processing. Prepared by – anuradha tAndon assistant professor , ic branch, ee department, it , nu. outline. Introduction Course content Teaching Methodology Evaluation Let’s get started. 1. Introduction. What is signal?

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introduction to digital signal processing

Introduction to Digital signal processing

Prepared by – anuradha tAndon

assistant professor,

icbranch, eedepartment,

it, nu

  • Introduction
  • Course content
  • Teaching Methodology
  • Evaluation
  • Let’s get started
1 introduction
1. Introduction
  • What is signal?
  • What is the difference between signal conditioning and signal processing?
  • Need for signal processing
  • Types of processing
  • Difference between analog and digital signal processing
  • Digital v/s. analog signal processing
what is signal
What is signal?
  • Anything which carries information
  • Examples are –
      • speech, is encountered in telephony, radio, and everyday life
      • biomedical signals, (heart signals, brain signals)
      • Sound and music, as reproduced by the compact disc player
      • Video and image,
      • Radar signals, which are used to determine the range and bearing of distant targets



What is signal?

  • In this course we shall adopt the following definition for the signal:

“a signal is defined as any physical quantity that varies with time, space or any other independent variable or variables” (Proakis and Manolakis)



What is the difference between signal conditioning and signal processing?

Input Electrical

Measurand Output

Fig. 1: Elements of Measurement System

Sensing Element

Signal Conditioning Element

Signal Processing Element


Source: NPTEL lecture notes, EE Department, IIT, Kharagpur


What is the difference between signal conditioning and signal processing?

  • A signal conditioning element converts one type of electronic signal into another type of signal.
  • Its primary use is to convert a signal that may be difficult to read by conventional instrumentation into a more easily read format.


Source: NPTEL lecture notes, EE Department, IIT, Kharagpur


What is the difference between signal conditioning and signal processing?

  • In performing this conversion a number of functions may take place.
  • They include:
          • Amplification
          • Electrical Isolation
          • Linearization
          • Cold junction compensation
          • Excitation

Source: (



What is the difference between signal conditioning and signal processing?

  • Signal processing is the challenge of extracting useful information from signals or more formally,
  • Signal processing is the analysis, interpretation, and manipulation of signals like sound, images, time-varying measurement values and sensor data etc…
  • For example biological data such as electrocardiograms, control system signals, telecommunication transmission signals such as radio signals, and many others.


need for signal processing
Need for signal processing
  • When a signal is transmitted from one point to another there is every possibility of contamination /deformation of the signal by external noise. So to retrieve the original signal at the receiver suitable filters are to be used, i.e., the signal is processed to obtain the pure signal.
  • Or in general, the processing of the signal helps to estimate characteristic parameters of the signal and also to transform the signal in to the desired form.
types of processing
Types of processing
  • Transformation
  • Filtering
  • Detection
  • Estimation
  • Recognition and classification
  • Coding (compression)
  • Synthesis and reproduction
  • Recording, archiving
  • Analyzing, modeling
categories of signal processing
Categories of signal processing
  • Depending on whether the signal is analog or digital, signal processing is categorized as analog signal processing and digital signal processing.
  • So, let’s first understand the analog and the digital signals.
analog signal processing
Analog signal processing
  • Analog signal processing if for signals that have not been digitized, as in classical radio, telephone, radar, and television systems.
  • This involves linear electronic circuits such as passive filters, active filters, additive mixers, integrators and delay lines.
  • It also involves non-linear circuits such as compander, multiplicators (frequency mixers and voltage-controlled amplifiers), voltage-controlled filters, voltage-controlled oscillators and phase-locked loops.
digital signal processing
Digital signal processing
  • Digital signal processing — for signals that have been digitized, processing is done by general-purpose computers or by digital circuits such as ASICs, field-programmable gate arrays or specialized digital signal processors (DSP chips).


digital signal processing1
Digital Signal Processing



Digital Signal out

Digital Signal in

Operation, Transformation performed

on digital signals (using a computer or

other special-purpose digital hardware)


digital signal processing2






Digital sampling of an analog signal:


Example of DSP algorithms is MAC:



Y =  ai * xi

i = 1

for (i = 1; i < count; i++){ sum += m[i] * n[i]; }

Digital Signal Processing
  • But what about analog signals?


digital and analog processing system example
Digital And analog Processing system example

x(n) and y(n)

are discrete signals

v(t) and vo(t)

are continuous signals

what is special about signal processing applications
What is Special about Signal Processing Applications?
  • Large number of samples being continuously fed to the system (samples or blocks).
  • Repetitive Operations:
    • The same operation being applied to different set of samples
    • Parallel processing
  • Vector and Matrix Operations
  • Real time operations
discussion on advantages of dsp
Discussion on Advantages of DSP
  • Accuracy: The analog circuits are prone to temperature and external effects, but the digital filters have no such problems.
  • Flexibility: Reconfiguration of analog filters is very complex whereas the digital filters can be reconfigured easily by changing the program coefficients.
  • Storage: Digital signals can be easily stored on any magnetic media or optical media are using semiconductor chips.


discussion on advantages of dsp1
Discussion on Advantages of DSP
  • Easy operation: Even complex mathematical operations can be performed easily using computers, which is not the case with analog processing.
  • Multiplexing: Digital signal processing provides the way for Integrated service digital network (ISDN) where digitized signals can be multiplexed with other digital data and transmitted through the same channel.
application areas
Application Areas

Image Processing Instrumentation/Control Speech/Audio Military

Pattern recognition spectrum analysis speech recognition secure communications

Robotic vision noise reduction speech synthesis radar processing

Image enhancement data compression text to speech sonar processing

Facsimile position and rate digital audio missile guidance

animation control equalization

application areas1
Application Areas

Telecommunications Biomedical Consumer applications

Echo cancellation patient monitoring cellular mobile phones

Adaptive equalization scanners UMTS

ADPCM trans-coders EEG brain mappers digital television

Spread spectrum ECG Analysis digital cameras

Video conferencing X-Ray storage/enhancement internet phone etc.

dsp techniques that will be covered in the course
DSP Techniques that will be Covered in the Course
  • Digital filtering for cleaning a signal from noise
  • Discrete Fourier transforms for finding a particular frequency component
  • Correlation techniques to find a signal buried in noise
  • Communications especially for filtering out noise
course content
Course Content
  • Signals & systems:
  • Introduction, classification of signals, Classification of discrete time signals and systems (energy signal & power signals), (periodic & nonperiodic), (even & odd signal), static & dynamic system, shift variant & invariant systems, linear & non-linear, causal & noncausal, stable & unstable systems, non-recursive & recursive, FIR & IIR systems, linear convolution, cross correlation & auto correlation.
  • Analysis of signals:
  • Fourier transform of discrete time signals, FT of standard signal & properties of FT, IFT Discrete Fourier Transform, Definition of DFT & IDFT, DFT of standard signals, properties of DFT, applications of DFT, FFT Algorithms, Introduction, properties of Wn, classification, Radix-2, FFT algorithm, Circular convolution


course content1
Course Content
  • Analysis of LTI systems:
  • ADC, sampling process, anti filter, quantization, Z- transform, properties of Z- Transform, Inverse ZTransform, Response of LT in Z domain with pole-zero representation, Stability & causality in terms of Z-transform.
  • Digital filters:
  • Difference between analog & digital filters, types of Digital filters, Design of FIR filters, Design of IIR filters, In comparison of IIR & FIR filters.


reference books
Reference Books
  • 1. Digital Signal Processing : Principles, Algorithms and Applications by J.G. Proakis and D.G. Manolakis
  • 2. Digital Signal Processing by S. Salivahanan, A. Vallavaraj & C. Gnanapriya
teaching scheme
Teaching Scheme
  • 4 credit course
  • 3 lectures/ week
  • 2 hours lab/ week
  • 2 class tests
  • 1 mid-semester examination
  • Term Paper is to be written as a part of special assignment (in group of 2 students only)
  • Term paper topics will be uploaded by August 15, 2014 on the course blog
  • The weightage of each component will be uploaded on the course website soon.
  • The course blog is
  • You will receive the invitation to follow the blog very soon.
  • (On line journal)
  • (rice university)
  • (lecture on DSP)
  • Lecture notes of Dr.Y. Narasimha Murthy Ph.D, Reader, Department of Physics & Electronics


concluding remarks
Concluding Remarks

The woods are lovely, dark and deep,But I have promises to keep,And miles to go before I sleep,And miles to go before I sleep. ---- Robert Frost