K-INFO
HU
EN
Login

Digital Filters

Digitális szűrők
A tantárgyleírás hatályossága
Hatályosság kezdete:
Hatályosság vége:
Subject name (Hungarian, English)
Digitális szűrők
Digital Filters
Subject code BMEVIMIM278
Subject type
Training Level
Course types and hours (weekly/semester)
Course type lecture tutorial laboratory
hours (weekly) 2 1 0
type (linked/independent) derived course
Assessment type vizsga
Credits 4
Subject coordinator
DR. Sujbert László
position: egyetemi docens
Responsible department
Faculty
Subject website http://www.mit.bme.hu/oktatas/targyak/vimim278/
Primary curriculum type
Direct prerequisites – Strong prerequisite none
Direct prerequisites – Weak prerequisite none
Direct prerequisites – Parallel prerequisite none
Direct prerequisites – Milestone prerequisite none
Direct prerequisites – Exclusion none

Objectives

Programme
Digital Filtering Problems. Digital filtering in information processing systems. Comparison of analog and digital filters.

 

Analysis and Synthesis Methods. Determination of the amplitude and phase response using analytic and numeric methods. Sensitivity analysis. Noise analysis. synthesis of linear networks. Analog to discrete transform of transfer functions. Matlab support.

 

Design of IIR Filters. Classical approximation methods: Butterworth, Chebishev, inverse Chebishev, elliptic filters. Frequency transforms. Design with least squares method. Design in the time domain. Filter order estimation. Matlab support.

 

Design of FIR Filters. The role of linear phase filters. Connection between the amplitude response and the impulse response. Design with frequency sampling. Design with windowing. Design with the Remes algorithm. Filter order estimation. Matlab support.

 

Special Digital Filters. Hilbert transformers. Gauss filters. Nonlinear filters, median filters. Matlab support.

 

Implementation. Problems of implementation: quantization, overflow, instability, limit cycles, noise. Digital filtering in common microprocessors and digital signal processors. Computational demand. Support offered by signal processors. Programming methods. Effective on-line and off-line methods. Signal processor support.

 

Implementation of FIR Filters. Transverse structure. Algorithms based on fast convolution. Filtering in the transform domain. Matlab and signal processor support.

 

Implementation of IIR Filters. Direct structure. Decomposition of the transfer function into second order blocks: cascade and parallel structure. Ordering of the blocks. Lattice structures. Wave digital filters. Resonator-based filters. Matlab and signal processor support.

 

The subject deals with the analysis, design and implementation of linear, time-invariant discrete-time filters. Application of digital filters requires deep knowledge of many theoretical and practical details. These problems are usually not discussed in detail in other courses. The aim of the subject is to give the most detailed review of the topic, from the mathematical basics to the programming methods. Although the learning of the theoretical background is inevitable, it is also an important goal to deliver practical skills. Therefore the review of the corresponding Matlab functions, and the digital signal processor based support of the implementation are also included in the program of the subject.     Students fulfilled the requirements of the subject are familiar with the possibilities of the application of digital filters; they can carry out the complete analysis of a filter with given transfer function; they know the most important design methods for finite and infinite impulse response filters. Having the high-level theoretical knowledge the students can use the high-level software support (Matlab functions); they can select the appropriate structure for the implementation. The students fulfilled the course are able to implement digital filters, especially using digital signal processors.  

Learning outcomes

Ez a tantárgy a KKK rendeletben meghatározott, következő kompetenciák fejlesztését szolgálja:

Knowledge

No learning outcomes recorded.

Skills

No learning outcomes recorded.

Attitudes

No learning outcomes recorded.

Autonomy and responsibility

No learning outcomes recorded.

Oktatási módszertan

2 hours/week lectures and 1 hour/week exercise.

Tanulástámogató anyagok

Online források
Simonyi Ernő, "Digitális szűrők. A digitális jelfeldolgozás alapjai", Műszaki Könyvkiadó, Budapest, 1984.; Parks, T. W., C. S. Burrus, "Digital Filter Design", John Wiley & Sons, New York, etc. 1987.

Recommended preliminary knowledge for completing the subject

Knowledge type competencies
(azon előzetes ismeretek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
nincs
Skill type competencies
(azon előzetes képességek és készségek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
nincs
Recommended (non-compulsory) preliminary competencies
(azon ajánlott (nem kötelező) előzetesen megszerzendő kompetenciák összessége, amelyek jelentősen hozzájárulnak a tantárgy eredményes teljesítéséhez)
nincs
General rules
Requirements: In the class period: 1 homework In the examination period: written exam Exam before the examination period: not available Additional possibilities: The homework can be submitted in the rectification period.
Assessment methods
In-term assessments

No detailed assessments provided.

Weight of in-term assessments

No weights provided.

Exam-period assessments

No detailed assessments provided.

Weight of exam elements

No weights provided.

Grade calculation

No grade thresholds provided.

Attendance requirements

No attendance requirements provided.

Rules for retake and resubmission

Not provided.

Short description

Not provided.

Detailed description

Not provided.

Recommended courses
Signal processing
Workload to complete the subject

No workload breakdown provided.

Validity of subject requirements
Requirements valid from:
Requirements valid until:
Curriculum placement

No curriculum placements recorded for this subject version.