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wiener Scilab Group Scilab Function wiener
NAME
wiener - Wiener estimate
CALLING SEQUENCE
[xs,ps,xf,pf]=wiener(y,x0,p0,f,g,h,q,r)
PARAMETERS
f, g, h : system matrices in the interval [t0,tf]
f =[f0,f1,...,ff], and fk is a nxn matrix
g =[g0,g1,...,gf], and gk is a nxn matrix
h =[h0,h1,...,hf], and hk is a mxn matrix
q, r : covariance matrices of dynamics and observation noise
q =[q0,q1,...,qf], and qk is a nxn matrix
r =[r0,r1,...,rf], and gk is a mxm matrix
x0, p0 : initial state estimate and error variance
y : observations in the interval [t0,tf]. y=[y0,y1,...,yf], and
yk is a column m-vector
xs : Smoothed state estimate xs= [xs0,xs1,...,xsf], and xsk is a
column n-vector
ps : Error covariance of smoothed estimate ps=[p0,p1,...,pf], and
pk is a nxn matrix
xf : Filtered state estimate xf= [xf0,xf1,...,xff], and xfk is a
column n-vector
pf : Error covariance of filtered estimate pf=[p0,p1,...,pf], and
pk is a nxn matrix
DESCRIPTION
function which gives the Wiener estimate using the forward-backward
Kalman filter formulation
AUTHOR
C. B.
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