Mercurial > hg > ltpda
view m-toolbox/classes/@ao/ngsetup.m @ 3:960fe1aa1c10 database-connection-manager
Add LTPDADatabaseConnectionManager implementation. Java code
author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Mon, 05 Dec 2011 16:20:06 +0100 |
parents | f0afece42f48 |
children |
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% NGSETUP is called by the function fromPzmodel % % Inputs calculated by ... % ... NGCONV: % - den: denominator coefficients % % ... USER % - fs: sampling frequency given as input to LTPDA_NOISEGEN % % Outputs: % - Tinit: matrix to calculate initial state vector % - Tprop: matrix to calculate propagation vector % - E: matrix to calculate propagation vector % % A Monsky 24-07-07 % % $Id: ngsetup.m,v 1.3 2008/10/20 08:38:29 anneke Exp $ function [Tinit,Tprop,E] = ngsetup(den,fs) den=den'; dt = 1/fs; length(den); n = length(den)-1; %% setting up matrix Aij m_a = zeros(n,n); for i = 1:n for j = 1:n if j == i+1 m_a(i,j) = 1; end if i == n m_a(i,j) = -den(j); end end end %% Matrix exponential E E = expm(m_a*dt); %% setting up matrix Bij B = zeros(n,n); for i=1:n if rem(i,2) ~= 0 j0 = (i+1)/2; s = (-1)^(j0+1); j = j0; for k=1:2:(n+1) B(i,j) = s*den(k); s = -s; j = j+1; end end if rem(i,2) == 0 j0 = i/2+1; s = (-1)^j0; j = j0; for k=2:2:(n+1) B(i,j) = s * den(k); s = -s; j = j+1; end end end %% solve B * m = k m_k = zeros(n,1); m_k(n) = 0.5; m_m = B\m_k; %% filling covariance matrix Cinit Cinit = zeros(n,n); for i=1:n for j=1:n if rem((i+j),2) == 0 % even Cinit(i,j) = (-1)^((i-j)/2) * m_m((i+j)/2); else Cinit(i,j) = 0; end end end %cholesky decomposition Tinit = chol(Cinit,'lower'); %lower triangular matrix %% setting up matrix D N = n*(n+1)/2; m_d = zeros(N); g = zeros(n); for i=1:n for j=1:n if i>=j g(i,j) = (i*i-i)/2+(j); else g(i,j) = (j*j-j)/2+(i); end end end for i=1:n for j=i:n for k=1:n m_d(g(i,j),g(j,k)) = m_d(g(i,j),g(j,k)) + m_a(i,k); m_d(g(i,j),g(i,k)) = m_d(g(i,j),g(i,k)) + m_a(j,k); end end end %% setting up q from D * p = q m_q = zeros(1,g(n,n)); for i=1:n for j=i:n if i==n m_q(g(i,j)) = (E(n,n))*(E(n,n))-1; else m_q(g(i,j)) = (E(i,n)*E(j,n)); end end end m_p = m_d\m_q'; Cprop = zeros(n); for i=1:n for j=1:n Cprop(i,j) = m_p(g(i,j)); end end Tprop = chol(Cprop,'lower'); % %% writing the generator % r = randn(n,1); % y = Tinit * r; % x = zeros(Nfft,1); % for i=1:Nfft % r = randn(n,1); % y = E * y + Tprop * r; % x(i) = a*y; % end end