MA 7165 STATISTICAL DIGITAL SIGNAL PROCESSING 
                           
         Total hours: 56                      L T P C 
                                              3 1 0 3 
         
         
         
        Module I: (15 hours)   
        Discrete-Time Random Processes: Random Variables, Random Processes, Filtering Random Processes, 
        Spectral Factorization, Special Types of Random Processes. 
         
        Module II: (12 hours) 
        Signal Modeling: The Least Squares Method, The Pade Approximtion, Prony’s Method, Finite Data 
        Records, Stochastic Models. 
         
        Module III: (14 hours) 
        Lattice Filters and Wiener Filtering: The FIR Lattice Filter, Split Lattice Filter, IIR Lattice Filters, 
        Stochastic Modeling, The FIR Wiener Filter, IIR Wiener Filter, Discrete Kalman Filter. 
         
        Module IV: (15 hours) 
        Spectrum Estimation: Nonparametric Methods, Minimum Variance Spectrum Estimation, The Maximum 
        Entropy Method, Parametric Methods, Frequency Estimation, Principal Components Spectrum 
        Estimation. 
         
        References:   
          1.  M. H. Hayes; “Statistical Digital Signal Processing and Modeling”,  John Wiley & Sons, 2004. 
          2.  G. J. Miao and M. A. Clements; “Digital Signal Processing and Statistical Classification”, Artech 
           House, London, 2002. 
          3.  R. M. Gray and L. D. Davisson ; “An Introduction to Statistical Signal Processing”, Cambridge 
           University Press, 2004.