DSP632 Digital Signal Processing: Introduction

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(DSP-632) Digital Signal Processing Introduction

• Presented by
• Neetesh Purohit
• Lecturer, IIIT,
• Allahabad, UP, India
• http//profile.iiita.ac.in/np/

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Distribution of Internal Marks

• Proportionate marks for attendance (10)
• Quiz marks (1010)
• Unsolved problems at the end of all chapters is
  an assignment. You should try to solve 5 problems
  within 2 days after completion of a particular
  chapter in your assignment copy. (15)
• The problem numbers will be (your roll number
  x) mod N x0,4,8,12,16 And N number of problems

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Signal

• A physical quantity that varies with time, space
  or any other independent variable(s).
• In all practical scenarios it should be an
  Information-bearing function. (what is
  information?)
• E.g. sound air pressure variation at a point as
  a function of time p(t)
• Dimensionality (no. of variables in the
  function)
• Sound 1-Dimension
• Greyscale image i(x,y) 2-D
• Video 3 x 3-D r(x,y,t) g(x,y,t) b(x,y,t)

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The role of signal in Comm. Systems
For a layman, information may be an idea in
someones mind or it may be a news that something
has been happened or will happen etc.

• Information Information

I/P Transducer
O/P Transducer
Electrical signal
Receiver
Transmitter
channel
Twisted Copper wire coaxial cable optical
fiber space
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Signal processing

• Modify a signal to extract/ enhance/ rearrange
  the information.
• Origin in analog electronics e.g. In RADAR, the
  purpose of processing includes -
• Noise reduction
• Data compression
• Representation for recognition/ classification

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Digital Signal Processing

• DSP Signal processing on a computer
• Two effects discrete-time, discrete level
• The Problem?

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Digital vs. Analog

• Advantages of Digital Signal Processor
• More flexible.
• Often easier system upgrade.
• Data easily stored.
• Better control over accuracy requirements.
• Reproducibility Cheaper

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• Limitations
• A/D signal processors speed
• Wide-band signals still difficult to treat
  (real-time systems).
• Finite word-length effect ( Round-off error
  caused by rounding math calculation result to
  nearest quantisation level.)

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Application areas

• Space (Photograph enhancement, Intelligent
  sensory analysis etc)
• Medical (CT, MRI, ultrasound etc.)
• Commercial (Image and sound compression etc.)
• Telephone (Echo reduction, data compression,
  Filtering etc.)
• Military (Radar, Sonar, secure communication
  etc.)
• Industrial (Process Monitoring and control etc.)

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The syllabus

• Unit I
• Review of signal and system theory
  Classification of discrete time signals and
  systems, The concept of frequency in CT and DT
  signals, Analysis of discrete time linear time
  invariant systems, Correlation of discrete time
  signals, Z-domain analysis.
• Unit II
• Fourier series and Fourier transform analysis of
  discrete signals and DTLTI systems, Inverse
  systems and deconvolution, Discrete Fourier
  transform, circular convolution and other
  properties of DFT, Linear Filtering based on DFT,
  frequency analysis of signals using DFT.

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• Unit III
• Fast Fourier Transform algorithms and their
  applications, Quantization effects in the
  computation of the DFT, Short Time Fourier
  Transform, Wavelet Transform.
• Unit IV
• Structures for IIR and FIR systems,
  representation of numbers, quantization of filter
  coefficients, round off effects, Design of
  digital filters, linear prediction and optimum
  linear filters.

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Books

• Text Book
• DSP Principles, algo and app, III edition
  authored by PROAKIS, PE.
• Reference book
• DTSP, II edition, authored by Oppenheim and
  Schafer, PHI.