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Please note that the recommended version of Scilab is 2026.0.0. This page might be outdated.
See the recommended documentation of this function
wiener
Wiener estimate
Calling Sequence
[xs,ps,xf,pf]=wiener(y,x0,p0,f,g,h,q,r)
Arguments
- f, g, h
- system matrices in the interval - [t0,tf]- f
- = - [f0,f1,...,ff], and- fkis a nxn matrix
- g
- = - [g0,g1,...,gf], and- gkis a nxn matrix
- h
- = - [h0,h1,...,hf], and- hkis a mxn matrix
 
- q, r
- covariance matrices of dynamics and observation noise - q
- = - [q0,q1,...,qf], and- qkis a nxn matrix
- r
- = - [r0,r1,...,rf], and- gkis a mxm matrix
 
- x0, p0
- initial state estimate and error variance 
- y
- observations in the interval - [t0,tf].- y=[y0,y1,...,yf], and- ykis a column m-vector
- xs
- Smoothed state estimate - xs= [xs0,xs1,...,xsf], and- xskis a column n-vector
- ps
- Error covariance of smoothed estimate - ps=[p0,p1,...,pf], and- pkis a nxn matrix
- xf
- Filtered state estimate - xf= [xf0,xf1,...,xff], and- xfkis a column n-vector
- pf
- Error covariance of filtered estimate - pf=[p0,p1,...,pf], and- pkis a nxn matrix
Description
function which gives the Wiener estimate using the forward-backward Kalman filter formulation
Authors
C. B.
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