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Advanced Digital Signal Processing Techniques

COURSE: Advanced Digital Signal Processing Techniques

Code: ФЕИТ05010

ECTS points: 6 ECTS

Number of classes per week: 3+0+0+3

Lecturer: Assoc. prof. Dimitar Taskovski

Subject of the course content: Brief revue of signal models. Definitions and basic properties of discrete transforms. Orthogonal discrete transforms: Fourier(DFT), Hartley(DHT), Karhunen-Loeve (KLT), Cosine (DCT), Lapped (LOT), wavelet(WLT), Walsh-Hadamard (WHT). Two- dimensional transforms. Fast algorithms: concept and selected examples. Applications in signal processing: filtering, spectral estimation, coding, adaptive filtering, multirate signal processing.

Introduction to the fundamental theory of multirate signal processing: decimation, interpolation, and sampling rate conversion, Two-channel filter banks: quadrature-mirror filter banks (QMF), perfectly reconstructing, paraunitary, biorthogonal and linear phase filter banks, M-channel filter banks used as subband coding or transmultiplexing filter banks. Polyphase structures for two-channel and M-channel filter banks. Lattice structures for Linear Phase PR QMF Banks, Discrete Wavelet Transform (DWT) and its relations to multirate filter banks. The Short-Time Fourier Transform. The Wavelet Transform. Discrete-Time Orthonormal Wavelets. Continuous-Time Orthonormal Wavelet Bases. Lifting implementations of wavelet transform Applications of wavelets for signal analysis and compression.

Literature:

  1. D. F. Elliot and K. Ramamohan Rao, Fast Transforms: Algorithms, Analyses, Applications
  2. P.P. Vaidyanathan, Multirate Systems and Filters Banks