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Full Version: DSP Algorithm & Architecture
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PART A
UNIT - 1
INTRODUCTION TO DIGITAL SIGNAL PROCESSING: Introduction, A Digital Signal-Processing System, The Sampling Process, Discrete Time Sequences, Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT), Linear Time-Invariant Systems, Digital Filters, Decimation and Interpolation.
5 Hours
UNIT - 2
ARCHITECTURES FOR PROGRAMMABLE DIGITAL SIGNAL-PROCESSORS: Introduction, Basic Architectural Features, DSP Computational Building Blocks, Bus Architecture and Memory, Data Addressing Capabilities, Address Generation Unit, Programmability and Program Execution, Features for External Interfacing.
8 Hours
UNIT - 3
PROGRAMMABLE DIGITAL SIGNAL PROCESSORS: Introduction, Commercial Digital Signal-processing Devices, Data Addressing Modes of TMS32OC54xx., Memory Space of TMS32OC54xx Processors, Program Control.
6 Hours
UNIT - 4
Detail Study of TMS320C54X & 54xx Instructions and Programming, On-Chip peripherals, Interrupts of TMS32OC54XX Processors, Pipeline Operation of TMS32OC54xx Processor.
6 Hours

UNIT - 5
IMPLEMENTATION OF BASIC DSP ALGORITHMS: Introduction, The Q-notation, FIR Filters, IIR Filters, Interpolation and Decimation Filters (one example in each case).
6 Hours
UNIT - 6
IMPLEMENTATION OF FFT ALGORITHMS: Introduction, An FFT Algorithm for DFT Computation, Overflow and Scaling, Bit-Reversed Index Generation & Implementation on the TMS32OC54xx.
6 Hours
UNIT - 7
INTERFACING MEMORY AND PARALLEL I/O PERIPHERALS TO DSP DEVICES: Introduction, Memory Space Organization, External Bus Interfacing Signals. Memory Interface, Parallel I/O Interface, Programmed I/O, Interrupts and I / O Direct Memory Access (DMA).
8 Hours
UNIT - 8
INTERFACING AND APPLICATIONS OF DSP PROCESSOR: Introduction, Synchronous Serial Interface, A CODEC Interface Circuit. DSP Based Bio-telemetry Receiver, A Speech Processing System, An Image Processing System.



Question Paper Pattern:
Student should answer FIVE full questions out of 8 questions to be set each carrying 20 marks, selecting at least TWO questions from each part.


Subject Overview:
• This subject will introduce students to real-time digital signal processing (DSP) applications, algorithms and hardware.
• The course aims to bridge the mathematics introduced in an undergraduate DSP course with practical implementation issues.
• The necessary interaction between hardware and software will be studied in the context of one DSP board, the TMS320C54XX using Code Composer Studio IDE.
• Fundamental compromises amongst computational accuracy, speed and cost and their relation to DSP architectural elements will be considered.
• Case studies involving real-time filter design and the implementation of common real-time audio, image and video processing algorithms will be explored.

Objectives:
On completion of this subject, students will be expected to:
 The ability to overcome technical obstacles through applying an idea of basic processor and resourcefulness;
 An appreciation of the importance of real-time DSP for a broad class of engineering applications; and a positive learning environment.
 To understand the issues involved in implementing DSP algorithms on processors.
 To understand and appreciate the features provided by various architectures in supporting common DSP tasks.
 To understand the implementation of common DSP tasks on processors.
Generic Skills / Outcomes:
On completion of this subject students will be able to:
 Be able to identify the basic architectural elements of DSP hardware;
 Understand common real-time DSP algorithms for filtering and multimedia processing applications;
 Be able to program DSP hardware to perform signal, image and video processing tasks using Code Composer Studio IDE.
 Gain an appreciation for the trade-offs necessary in algorithm design for real-time DSP implementation.
 Be able to learn FFT algorithms and write a corresponding program of DSP processor of TMS 5416xxx

Breadth Options
 This subject potentially can be taken as a breadth subject component for the following courses: Bachelor of Engineering specialization in ECE.
 Engineering science students develop skills in systems design with a high level of scientific knowledge.

Prerequisite:
 The prerequisite subject of this subject are signals & systems, Digital signal processing, microprocessors and one assembly level language.