Digital Signal Processing & Digital Filters ppt slides
By Professor A G Constantinides
Contents
1) Introduction
n Review of background DSP
n Review of mathematical methods
n Review of discrete-time random processes and linear systems
2) Multirate techniques and wavelets
n Introduction to short-time Fourier analysis
n Filter-banks and overlap-add methods of analysis and synthesis
n Introduction to generalised time-frequency representation
n Wavelet analysis
n Multirate signal processing
n Interpolation and decimation
n Efficient filter structures for interpolation and decimation
3) Classical spectrum estimation methods
n Power spectrum, power spectral density functions, random processes and linear systems
n Introduction to statistical estimation and estimators
n Biased and unbiased estimators
n Einstein/Wiener Khintchine Theorem
n Estimation of autocorrelations
n Means and variances of periodograms
n Smoothed spectral estimates, leakage
4) Modern spectrum estimation methods
n Introduction to modern spectral estimation: Principles and approaches
n Cramer-Rao Lower Bound (CRLB) and Efficient estimators
n The Maximum Entropy Method (MEM) or Autoregressive Power Spectrum Estimation: Principles.
n The MEM equations and Levinson/Durbin algorithm
n Introduction to Linear Prediction
n Linear Predictive Coding using covariances and correlations
n Cholesky decomposition
n Lattice Filters
n Linear Prediction of Speech Signals
5) Adaptive signal processing
n Introduction to adaptive signal processing
n Objective measures of goodness
n Least squares and consequences
n Steepest descent
n The LMS and RLS algorithms
n Kalman Filters
6) Applications
§ Communications
§ Biomedical
§ Seismic
§ Audio/Music
Lecture Slides Download here
Chapter 1 :
Introduction
Chapter 2 :
Chapter 3 :
Chapter 4 :
Chapter 5 :
Chapter 6 :
Chapter 7 :Chapter 8 :
Applications Part 1
Applications Part 2Background Information :
Background DSP Information :
Background Mathematical Information :
Chapter 1 - Signal Spaces
Chapter 2 - Linear Transformations
