| December 24th, 2020 10:57 AM | |
| ReenaK | Sathyabama Institute of Science and Technology M.E. - Applied Electronics SECA7036 Time Frequency Analysis Syllabus Sathyabama Institute of Science and Technology M.E. - Applied Electronics SECA7036 Time Frequency Analysis Syllabus SATHYABAMA INSTITUTE OF SCIENCE AND TECHNOLOGY SCHOOL OF ELECTRICAL AND ELECTRONICS ENGINEERING SECA7036 TIME FREQUENCY ANALYSIS L T P Credits Total Marks 3 0 0 3 100 UNIT 1 INTRODUCTION TO TIME FREQUENCY ANALYSIS 9 Hrs. Introduction to time frequency analysis- Basic definitions and concepts-Continuous time Fourier series and Fourier transform -Discrete-Time Fourier Series Discrete-Time Fourier Transform Discrete Fourier Transform & Periodogram-Bandwidth Equation Instantaneous Frequency Analytic Signals Multicomponent Signals UNIT 2 BASES FOR TIME-FREQUENCY ANALYSIS STFT 9 Hrs. Duration-Bandwidth Principle – Band width equation and Instantaneous frequency-Requirements of time frequency analysis techniques-STFT: Definition and Interpretations- Uncertainty Principle, Localization/Isolation in time and frequency- General Properties - Theorem and need for joint time-frequency Analysis- Concept of non-stationary signals- STFT: Application UNIT 3 WIGNER VILLE DISTRIBUTION 9 Hrs. WVD: Definition and Interpretations - Properties of WVD- Discrete WVD- Pseudo and smoothed WVD- Cohen’s class - Connections with Spectrogram -WVD: Application UNIT 4 WAVELET TRANSFORM 9 Hrs. CWT: Definition and Interpretations –Scale to frequency- Computational aspects of wavelets CWT -TFA and Filtering Perspective- Scalogram- Scaling Function –Wavelets- CWT: Application -DWT: Definition and Interpretations- Orthonormal Bases and Multiresolution Approximation- Wavelet filter and fast DWT algorithm-Wavelets for DWT-Applications of wavelets UNIT 5 HILBER HUANG TRANSFORM 9 Hrs. The Hilbert-Huang transform- The empirical mode decomposition method (the sifting process)- The Hilbert spectral analysis- Confidence limit- Statistical significance of IMFs- Mathematical problems related to the HHT- EMD Equivalent Filter Banks.- Denoising and detrending with EMD Max. 45 Hrs. COURSE OUTCOMES On completion of the course, students are able to CO1 - Understand the basics of Fourier transform and importance of Time frequency analysis CO2 - Understand Short Time Fourier Transform and Duration Bandwidth principle CO3 - Explain the concept of Wigner Ville Distribution CO4 - Explain both CWT and DWT CO5 - Explain the concept of HHT principle and its applications CO6 - Apply the concept of Time frequency Analysis for Nonstationary signal processing applications. TEXT / REFERENCE BOOKS 1. S. Mallat, "A Wavelet Tour of Signal Processing", Academic Press, 3rd Edition, 2009. 2. L. Cohen, “Time-frequency analysis”, Prentice Hall, 1995. 3. B. Boashash, "Time-Frequency Signal Analysis and Processing: A Comprehensive Reference", Elsevier Science, 2003, ISBN-13: 978- 0080443355. 4. R.M. Rao and A.S. Bopardikar, "Wavelet Transforms: Introduction to Theory & Applications", Prentice Hall, 1998, ISBN- 13: 978- 0201634631. END SEMESTER EXAMINATION QUESTION PAPER PATTERN 1. Max. Marks: 100 Exam Duration: 3 Hrs. PART A: 5 Questions of 6 marks each - No choice 30 Marks PART B: 2 Questions from each unit of internal choice, each carrying 14 marks 70 Marks |
