2D AR and 2D ARMA parameters estimation 1.0

The 2D ARMA estimation algorithm is the implementation of the approach proposed in "Two-dimensional ARMA modeling for breast cancer detection and classification" by N. Bouaynaya, J. Zielinski and D. Shonfeld.Content:- arma2Ddemo: See and run the demo 'arma2Ddemo' for an example of 2D AR and ARMA parameters estimation from simulated images.- sim_ar2d: generation of simulated 2D AR process.- sim_arma2d: generation of simulated 2D ARMA process.- ar2d: solves 2D yule walker to estimate AR parameters- arma2d: estimation of 2D ARMA parameters. First step: estimation of the gaussian input by inv_ar2d, Second step: linear system solution to estimates simultaneously AR and MA parameters, as explained in [1].- inv_ar2d: first step in arma2d. Filters through inverse filter 1/AR an AR process, to generate its innovation Gaussian signal. It is used here to estimate the Gaussian noise input to the ARMA 2D process, approximating the ARMA model to a high order AR model.- poles2coeff: converts poles chosen by user to AR or MA coefficients (support function)References:[1]. "Two-dimensional ARMA modelling for breast cancer detection and classification" by N. Bouaynaya, J. Zielinski and D. Shonfeldin IEEE International Conference On Signal Processing And Communications, Bangalore, India, July 2010

Requirements:	No special requirements
Platforms:	Matlab
Keyword:	Approximating,  Filter,  Gaussian,  Generate,  Innovation,  Inverse,  Model,  Noise,  Signal,  Simultaneously
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