EC2030 ADVANCED DIGITAL SIGNAL PROCESSING L T P C
3 0 0 3
UNIT I DISCRETE RANDOM PROCESS 9
Discrete random process – Ensemble averages, Stationary and ergodic processes,
Autocorrelation and Autocovariance properties and matrices, White noise, Power
Spectral Density, Spectral Factorization, Innovations Representation and Process,
Filtering random processes, ARMA, AR and MA processes.
UNIT II SPECTRAL ESTIMATION 9
Bias and Consistency, Periodogram, Modified periodogram, Blackman-Tukey method,
Welch method, Parametric methods of spectral estimation, Levinson-Durbin recursion.
UNIT III LINEAR ESTIMATION AND PREDICTION 9
Forward and Backward linear prediction, Filtering - FIR Wiener filter- Filtering and linear
prediction, non-causal and causal IIR Wiener filters, Discrete Kalman filter.
UNIT IV ADAPTIVE FILTERS 9
Principles of adaptive filter – FIR adaptive filter – Newton’s Steepest descent algorithm –
Derivation of first order adaptive filter – LMS adaptation algorithms – Adaptive noise
cancellation, Adaptive equalizer, Adaptive echo cancellors.
UNIT V ADVANCED TRANSFORM TECHNIQUES 9
2-D Discrete Fourier transform and properties– Applications to image smoothing and
sharpening – Continuous and Discrete wavelet transforms – Multiresolution Analysis –
Application to signal compression.
TOTAL= 45 PERIODS
1. Monson H Hayes,” Statistical Digital Signal processing and Modeling”, Wiley Student
Edition, John Wiley and Sons, 2004.
2. R.C. Gonzalez and R.E. Woods, “ Digital Image Processing”, Pearson, Second
1. John G Proakis and Manolakis, “ Digital Signal Processing Principles, Algorithms and
Applications”, Pearson, Fourth Edition, 2007.
2. Sophocles J. Orfanidis, Optimum Signal Processing, An Introduction, McGraw Hill,1990.