Digital Signal Processing Applications

Updated on 2017/07/26 20:26

Digital signal processing (DSP) and Analog signal processing are subfields of signal processing. DSP means the use of digital processing, such as by computers, to perform a wide variety of signal processing operations. The signals processed in this manner are a sequence of numbers that represent samples of a continuous variable in a domain such as time, space, or frequency.
DSP applications include audio and speech signal processing, sonar, radar, sensor array processing and much more.



Digital Signal Processing Applications


Third Year, Semester II



Examination Scheme

Phase I: In Semester Assessment30
Phase II: End Semester Examination70

Course Objectives

  • Study and understanding of representation of signals and systems.
  • To learn and understand different Transforms for Digital Signal Processing
  • Design and analysis of Discrete Time signals and systems
  • To Generate foundation for understanding of DSP and its applications like audio, Image, telecommunication and real world 

Course Outcomes

  • Students will understand the mathematical concepts of signal representation and transformations with their analysis.
  • Development of ability for generating proper solution to signal processing problems.
  • Students will be capable of understanding Digital Signal Processing Applications and
    implementation of signal processing to various applications.

Syllabus and Notes

Unit 1: Introduction

[Main Page: Introduction]

The Breadth and Depth of DSP, Statistics, Probability and Noise, How digital signal is created: ADC and DAC, Signals, Linear Systems, Classification of signals, Properties of DT systems, Mathematical models for representation of DT system: Linear convolution, Linear constant coefficient difference equation, Use of Transducers in Signal Processing, Analog to Digital conversions (ADC), Sampling Process.

Unit 2: Fourier Transform

[Main Page: Fourier Transform]

DTFT, Properties, DFT, Circular convolution, DFT Spectral leakage, Efficient computations of DFT, Fast Fourier Transform, Radix-2 DIT and DIF FFT Algorithms, Application of DFT, Linear filtering.

Unit 3: Z-Transform

[Main Page: Z-transform]

Definition of Z-Transform, ZT and FT, ROC, ZT properties, pole-zero plot, Inverse Z-Transform, Methods, System function H(Z), Analysis of DT LTI
systems in Z-domain: DT system representation in time and Z domain. Relationship of FT and ZT

Unit 4: Introduction to Filters

[Main Page: Introduction to Filters]

Filter Structures, components of digital filters, DT Filters Block diagram representation, equivalent structures, Basic FIR and IIR Filter structures, DT filters as DT systems, Solution of difference equation, FIR and IIR filters direct form structures, 

Unit 5: DSP Processors and Applications

DSP Processors

[Main Page: DSP Processors]

DSP Building Blocks, Data Acquisition, Fix Point and Floating Point Implementation the SHARC floating Point processor, SIMD Micro Architecture and Instructions, Operating systems, Micro-Architecture consideration, Implementation Options, Intrinsic and Data type, OMAP (Open Multimedia Application Platform)

DSP Applications

[Main Page: DSP Applications]

DSP and its benefits, Application areas, Key DSP operations, DSP processors, real world, audio, telecommunication applications and biomedical applications. 

Unit 6: DSP in Speech Processing & Image Processing

[Main Page: DSP in Speech Processing & Image Processing]

Audio Processing

Human Hearing, Timbre, Sound Quality Versus Data rate, High Fidelity Audio, Companding, Speech Synthesis and Recognition, Non Linear Audio Processing 

Image Foundation and Display

Digital Image Structure, Cameras and Eyes, Television Video Signals, Other Image Acquisition and display, Brightness and Contrast Adjustments, Gray Scale Transforms

Previous Years Question Papers


  • UniPune
  • Wikipedia
  • Icon by Arthur Shlain and VishalE
Created by Vishal E on 2017/05/06 19:22