Course detail

Digital Signal Processors

FEKT-LSPRAcad. year: 2017/2018

Definition of digital signal processor, its differences from the other microprocessors. Generations of digital signal processors and their typical features, trends of development. Basic digital signal processor architectures – the Harvard architecture, the VLIW architecture. Fixed- and floating-point number formats, IEEE-754 standard. Fixed-point digital signal processor of the TMS320C6400 series. Processor core, functional units, register set, addressing modes. Instruction set and the way it is applied. Link between programming in assembler and in the C language, intrinsic function, pragma expressions. Canonic and non-canonic structures for implementing FIR and IIR digital filters in digital signal processors, analysis of quantization noise, Mason’s rule, transfer function modification regarding fixed-point representation. Adaptive LMS algorithm and its implementation. Generation of harmonic signal and harmonic analysis, Goertzel's algorithm, structure of FFT algorithm and its types. Sum of peripherals, memory mapping, communication with external peripheries, direct memory access DMA. Real-time processing, circular buffer, double buffering.

Language of instruction

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

Guarantor

doc. Ing. Petr Sysel, Ph.D.

Department

Department of Telecommunications (UTKO)

Learning outcomes of the course unit

Students will be able to:
- explain the meaning of the parameters of microprocessors and digital signal processors, and choose a processor suitable for the application,
- explain the progress of the translation of separate C language source files including linking with other libraries,
- prepare the quantized coefficients of a digital system
- check the stability of the digital system after coefficient quantization,
- design a suitable form to implement the fixed point algorithm,
- analyze the effect of quantization in the structure and assess a suitable structure in terms of quantization,
- consider the advantages of the fast Fourier transform algorithm and Goertzel’s algorithm
- use the direct memory access (DMA) to transfer the samples in real time.

Prerequisites

The knowledge of digital signal processing and microprocessor technology is required. Students should be able to:
- describe the function of the basic blocks of the microprocessor (CPU, memory, I / O circuits, etc.)
- explain the basic commands of ANSI C,
- apply the basic commands of the ANSI C language and implement a simple program,
- calculate in terms of numbers the different number systems (binary, hex),
- explain the course of sampling the continuous signal
- explain the importance of stability,
- apply the Fourier transform.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Teaching methods depend on the type of course unit as specified in article 7 of the BUT Rules for Studies and Examinations.

Assesment methods and criteria linked to learning outcomes

Evaluation of study results follows the Rules for Studies and Examinations of BUT and the Dean's Regulation complementing the Rules for Studies and Examinations of BUT.
Solution of seven homework assignments max. 40 marks
Written examination max. 60 marks

Course curriculum

1. Generations of digital signal processors, common properties of digital signal processors, von Neumann's architecture, the Harvard architecture, parallel processing and VLIW architecture.
2. Fixed-point and floating-point representations, representations of negative numbers, properties of fixed-point digital signal processors.
3. Architecture of digital signal processors of the TMS320C6400 series by Texas Instruments, processor core, functional units, registers, specific instructions.
4. Address generation unit, modulo addressing mode.
5. Program structure and writing in assembler.
6. Program structure and writing in the C language, intrinsic functions, pragma directives, integrated development environment.
7. Program Controller, instruction pipeline.
8. Quantization effects on digital filters characteristics, limit cycles, optimization of digital filters in digital signal processors.
9. FIR and IIR digital filter implementation in digital signal processors.
10. Generation of harmonic signals and harmonic analysis, the Goertzel algorithm, implementation of the fast Fourier transform.
11. On-chip peripherals, DMA controller, interrupt controller.
12. External buses, external memory interface.
13. Floating-point digital signal processors.

Work placements

Not applicable.

Aims

The aim of the course is to introduce students to the architecture and basic properties of fixed- and floating-point digital signal processors, to describe the method of assembler programming, and to outline the connection with higher programming languages. Also covered is the implementation of algorithms of linear and adaptive digital filtering.

Specification of controlled education, way of implementation and compensation for absences

Lectures are not obligatory
Computer exercises are obligatory
Individual homeworks is obligatory
Written examination is obligatory

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Smékal, Z., Sysel, P. Signálové procesory. 1. vydání. Praha: Sdělovací technika, 2006. 283 s. ISBN 80-86645-08-8 (CS)

Recommended reading

SMÉKAL, Z., VÍCH, R.: Signal Processing on Digital Signal Processors (Zpracování signálů se signálovými procesory). Radix spol. s.r.o, Praha 1998. ISBN 80-86031-18-7 (In Czech) (CS)

Classification of course in study plans

  • Programme EEKR-ML Master's

    branch ML-BEI , 2. year of study, winter semester, optional interdisciplinary

  • Programme EEKR-CZV lifelong learning

    branch ET-CZV , 1. year of study, winter semester, optional specialized

Type of course unit

 

Lecture

39 hours, optionally

Teacher / Lecturer

doc. Ing. Petr Sysel, Ph.D.

Syllabus

1. Definition of digital signal processor, features that distinguish it from the other microprocessors. Generations of digital signal processors , their outstanding features, trends of development. Basic architectures of digital signal processors: von Neuman and Harvard architectures, type LIW and VLIW architectures, parallel systems.
2. Texas Instruments fixed-point digital signal processors. Processor core and the sum of peripherals. Storage mapping. Development tools. Instruction file and the way it is applied. Basic types of operations, pipelining, macro-commands and subprograms. Connection with programming in the C-language. Integer and fraction formats expressed in the ALU unit and in the memory. Saturation arithmetic, rounding. Addressing unit modes, modulo and reverse-bit addressing.
3. Canonic and non-canonic structures for the implementation of type IIR and FIR filters on digital signal processor. Description via signal flow graphs, Mason's rule. Introduction of initial conditions, connection with implementation. Effect of initial conditions on total response. Adaptive filtering on digital signal processor. Type LMS algorithm and its implementation. Example of application.
4. Generation of harmonic signal and harmonic analysis. Goertzel's algorithm. Structure of FFT algorithm and its types. Adapting the FFT algorithm for implementation on digital signal processor. Real-time spectral analysis with FFT on digital signal processor. Power spectral desnity and its calculation.
5. Peripherals of digital signal processor, co-processors, direct access to memory, structure of control unit, interrupt, type DO cycle, stack, on-chip emulation, JTAG. Floating-point digital signal processors and their distinctive features. IEEE-754 Standard, formats of fixed- and floating-point numbers. Subdividing the ALU unit into several parts. Examples of application.

Laboratory exercise

26 hours, compulsory

Teacher / Lecturer

doc. Ing. Petr Sysel, Ph.D.

Syllabus

1. Code Composer Studio, basic assembler directives. Fixed-point arithmetic, multiplication, saturation, rounding. Core of TMS320C6416 digital signal processor, examples of using core registers. Implementation of polynomial functions.
2. Implementation of FIR digital filters. Implementation of IIR digital filters.