Adaptivní zpracování signálů
Code | Completion | Credits | Range | Language |
---|---|---|---|---|
XE31ADA | Z,ZK | 4 | 2+2s |
- The course is a substitute for:
- Adaptive Filtering (X31ADA)
- Lecturer:
- Tutor:
- Supervisor:
- Department of Circuit Theory
- Synopsis:
-
The aim of this subject is to give the overview of adaptive filtering methods and their applications to speech and biological signal processing, noise cancellation, signal separation and signal analysis. Seminars are devoted to the implementation of algorithms in MATLAB. It is highly recommended to be acknowledged with the bases of digital signal processing.
- Requirements:
-
The elaboration and representation of one selected problem is the condition for the credit.
- Syllabus of lectures:
-
1. Batch and recursive signal analysis, basic terms
2. Batch parametric methods, least squares
3. Recursive parametric methods, accuracy of estimation
4. Memory shaping, RLS and LMS algorithms, properties
5. Estimation and signal modelling, RLS/LMS FIR estimator
6. Adaptive line enhancement, conditions, application to speech
7. Analysis of LMS algorithm, error surface, stability, equalization
8. Modifications of LMS algorithm, gradient noise, convergence
9. Narrow-band signal separation, LMS FIR/CIIR, resonator
10. Noise compensation, conditions of proper function
11. Symmetric adaptive structures for sources separation
12. Hyperstabil algorithms, LMS IIR, applications
13. Frequency domain adaptive filters, echo compensation
14. Adaptive filters with fast convergence
- Syllabus of tutorials:
-
1. Introduction to MATLAB, basic sequences generation
2. Short-time spectral analysis, spectrograms
3. Parametric methods, basic functions
4. Signal analysis using parametric methods
5. Synthesis of AR nonstationary processes and their analysis
6. Implementation of LMS estimator
7. Implementation of LMS predictor, noise suppression
8. Application of LMS algorithm for equalization
9. Comparison of LMS, SLMS, NLMS and RLS algorithms
10. Convergence behaviour of adaptive filters
11. Frequency analysis with application to speech formants
12. Implementation of noise cancellation methods
13. Implementation of frequency domain LMS adaptive filter
14. Projects presentation, credit
- Study Objective:
- Study materials:
-
1. Haykin, S.: Adaptive Filter Theory. Prentice-Hall, Inc., New Jersey, 1991
2. Widrow, B., Stearns, S.D.: Adaptive Signal Processing. Prentice-Hall, Inc., New Jersey, 1985
3. Young, P.: Recursive Estimation and Time-Serie Analysis, Springer-Verlag, New York, 1984
- Note:
- Further information:
- No time-table has been prepared for this course
- The course is a part of the following study plans: