deleted *~ files

1 files changed, 0 insertions, 49 deletions

diff --git a/macros/schurrc.sci~ b/macros/schurrc.sci~
deleted file mode 100644
index 71beb39..0000000
--- a/macros/schurrc.sci~
+++ /dev/null
@@ -1,49 +0,0 @@
-//schurrc - Schur algorithm.
-//K = SCHURRC(R) computes the reflection coefficients from autocorrelation vector R. If R is a matrix, SCHURRC finds coefficients for each column of R, and returns them in the columns of K.
-//[K,E] = SCHURRC(R) returns the prediction error variance E. If R is a matrix, SCHURRC finds the error for each column of R, and returns them in the rows of E.
-//Modified to match matlab i/p and o/p and handle exceptions
-//Fixed bugs
-//by Debdeep Dey 
-function [k,e] = schurrc(R)
-    narginchk(1,1,argn(2));
-if(type(R)==10) then
-    w=R;
-    [nr,nc]=size(R);
-    if(nr==1 & nc==1) then
-        R=ascii(R);
-        R=matrix(R,length(w));
-    else
-        
-        R=ascii(R);
-        R=matrix(R,size(w));
-    end
-    
-end
-if(type(R) > 1) then
-	error('Input R is not a matrix')
-end
-if (min(size(R)) == 1) then 
-    R = R(:); 
-end 
-[m,n] = size(R);
-// Compute reflection coefficients for each column of the input matrix
-for j = 1:n
-	X = R(:,j).';
-	// Schur's iterative algorithm on a row vector of autocorrelation values
-	U = [0 X(2:m); X(1:m)];
-
-    for i = 2:m,
-        U(2,:) = [0 U(2,1:m-1)];    
-        k(i-1,j) = -U(1,i)/U(2,i); 
-        U = [1 k(i-1,j); conj(k(i-1,j)) 1]*U;
-    end
-   
-	e(j,1) = U(2,$);
-end
-endfunction
-function narginchk(l,h,t)
-    if t<l then
-        error("Too few input arguments");
-    elseif t>l then
-        error("Too many i/p arguments");
-    end