# 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.

## Overview

Digital Signal Processing Applications

AbbreviationDSP
Course

Third Year, Semester II

CE

Credits

Examination Scheme

 Phase I: In Semester Assessment 30 Phase II: End Semester Examination 70
LanguageEnglish

## 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

## References

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

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