Course detail
Digital Filters
FEKT-BCIFAcad. year: 2012/2013
The course covers the whole range of the digital signal processing, from real-time implementation of digital systems, through methods of the analysis of one-dimensional digital systems, up to the basic methods of designing one-dimensional digital filters: representation of numbers, floating- and fixed-point arithmetic, the Harvard architecture of digital signal processors, very long instruction word (VLIW) architecture, programming processors in the assembler and in the C language(intrinsic functions, pragma directives, pre-processor directives, linker), real-time communication with off-chip peripherals, characteristics of digital systems (transfer function, impulse response, frequency response), stability and causality of digital systems, finite and infinite impulse response, the structures of digital systems, signal flow graphs, the effect of quantization on the digital system characteristics, methods of designing one-dimensional digital filters, systems with multiple sample rates, filter banks.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Learning outcomes of the course unit
* Overview of the technical devices in which the digital systems are implemented,
* overview of the various generations of digital signal processors and their properties,
* experience with the implementation of digital signal processing algorithms using fixed-point arithmetic,
* experience with the programming microcontrollers in the C language,
* practical experience with the implementation of real-time digital signal processing,
* practical experience with the design of digital filters.
Experience can be in particular utilized:
* When optimizing digital signal processing algorithms,
* when programming the microprocessor,
* when the development of telecommunication equipment.
Prerequisites
* Computers and Programming 2 (BPC2)
* Signals and Systems Analysis (BASS)
* Digital Circuits and Microprocessors (BDOM)
* Digital Signal Processing (BCZS).
Co-requisites
Planned learning activities and teaching methods
Lectures have the explanation of basic principles, methodology of the discipline problems and their solutions.
Practice proceeds on digital signal processor development kits and Matlab.
Assesment methods and criteria linked to learning outcomes
Test practice max. 10 marks
Check exercises max. 15 marks
Self-dependent project max. 15 marks
Written examination max. 60 marks
Course curriculum
2. Programming processors in the C language, the compilation process, the pre-processor directives, linking stage, intrinsic functions, assembler language, linking assembler and the C language.
3. The communication of the digital signal processor with off-chip peripherals, connecting the A / D and D / A converters, circular buffering, double buffering, interrupt handling, the controller program.
4. Description of digital system, difference equations, transfer functions, zeros, poles, state-space description, signal flow graph, Mason's rule, the basic characteristics of digital systems, frequency response, impulse response, stability.
5. Floating-point arithmetic, fixed-point arithmetic, dynamic range, saturation, quantization noise, arithmetic logical unit, analysis of quantization effects on the transfer function and other characteristics of digital systems, limit cycles.
6. Structures for the realization of digital systems, canonical forms of realization, the classification of digital systems, digital systems with finite impulse response (FIR) and infinite impulse response (IIR).
7. Hardware cycles, address generation unit, addressing modes, utilization of addressing modes in the C language and assembler, optimization of digital systems, code profiling.
8. Design of FIR digital filters: Window method, frequency sampling method, optimum equiripple linear phase filter design method, Remez's algorithm.
9. Design of IIR digital filters: a method of bilinear transformation, method of impulse invariance. Conversion to the second-order section.
10. Inverse filtering, Wiener optimal filtering, the Wiener-Hopf equation. Adaptive filters, LMS algorithm, RLS algorithm, properties and applications of adaptive filters.
11. Multi-rate systems, decimation and interpolation, sampling-rate conversion by a rational number, polyphase filter structures.
12. Filter banks, DFT filter bank, filter bank modulated by cosine function, two-channel filter bank, perfect reconstruction condition, quadrature mirror filters.
13. Fundamentals of nonlinear digital signal processing, filters based on sorting, homomorphic filtering, cepstral analysis.
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Computer exercise are duly
Self-dependent project is duly
Written examamination is duly
Recommended optional programme components
Prerequisites and corequisites
Basic literature
Recommended reading
Classification of course in study plans
- Programme ZRZT-J Bachelor's
branch J-ZRT , 3 year of study, summer semester, elective specialised
- Programme EECC Bc. Bachelor's
branch B-TLI , 3 year of study, summer semester, elective specialised
- Programme EEKR-CZV lifelong learning
branch EE-FLE , 1 year of study, summer semester, elective specialised
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
2. Causal and stability of linear time invariant systems, stability test. Definition of frequency response, digital filters as basic frequency-selective filters, zero and pole location. Linear phase frequency response.
3. Structures for realization for digital filters, first and second direct form, first and second transposed form. Signal flow graphs for digital filters description, analyses of signal flow graph by Mason's rule.
4. Fixed- and floating-point representation of numbers, accuracy and dynamic range, representation of negative numbers. Quantization effects on transfer function, on frequency response, on zeros and poles location. Limit cycles. Analysis of quantization errors.
5. Preparation of transfer functions for implementation in technical devices, dividing of high-order transfer function into second order sections. Hardware for implementation of digital filters, examples of implementation of FIR and IIR filters.
6. Design of FIR type digital filters. Method of windowing, method of frequency response sampling.
7. Optimum uniform rippled filters, alternation theorem, Remez's algorithm. Design of special kind of digital filters - differentiators, Hilbert's transformers.
8. Design of IIR digital filters. Making use of analog prototypes. Methods of bilinear transformation and impulse invariance.
9. Computer based method of IIR digital filters design, least-squares method. Inverse filtering.
10. Optimal Wiener filtration, Wiener-Hopf equation. Adaptive filters, LMS algorithms, RLS algorithms.
11. Multirate systems, decimation and interpolation, change in sampling frequency in the form of rational fraction.
12. Filter banks, perfect reconstruction condition, quadrature mirror filters. Wavelet transform.
13. Nonlinear digital filters, polynomial digital filters, filters based on sorting. Homomorphous filtering, real and complex cepstrum.
Laboratory exercise
Teacher / Lecturer
Syllabus
2. Digital filter types, measurement of frequency response and impulse response.
3. Design and implementation of finite impulse response digital filters using windows, digital signal filtering.
4. Design and implementation of FIR digital filters by the frequency-sampling method.
5. Design and implementation of optimum equiripple FIR digital filters.
6. Design and implementation of infinite impulse response digital filters by the bilinear transformation.
7. Design and implementation of IIR digital filters by impulse invariance.
8. Canonic structures, measurement of influence of initial conditions.
9. Fixed point and floating point representation of numbers, measurement of influence of quantization.
10. Adaptive filtering, measurement of convergence and stability.
11. Sampling rate conversion, implementation of sampling rate conversion by rational factor.
12. Nonlinear methods, homomorphic deconvolution.
13. Classification of individual projects.