Scilab 5.3.0
- Manuel Scilab
- Traitement du Signal
- How to
- Signal
- analpf
- bilt
- buttmag
- casc
- cepstrum
- cheb1mag
- cheb2mag
- chepol
- convol
- corr
- cspect
- czt
- detrend
- dft
- ell1mag
- eqfir
- eqiir
- faurre
- ffilt
- fft
- fft2
- fftshift
- filt_sinc
- filter
- find_freq
- findm
- frfit
- frmag
- fsfirlin
- group
- hank
- hilb
- hilbert
- iir
- iirgroup
- iirlp
- intdec
- jmat
- kalm
- lattn
- lattp
- lev
- levin
- lindquist
- mese
- mfft
- mrfit
- %asn
- %k
- %sn
- phc
- pspect
- remez
- remezb
- rpem
- sincd
- srfaur
- srkf
- sskf
- syredi
- system
- trans
- wfir
- wiener
- wigner
- window
- yulewalk
- zpbutt
- zpch1
- zpch2
- zpell
Please note that the recommended version of Scilab is 2025.0.0. This page might be outdated.
See the recommended documentation of this function
srkf
square root Kalman filter
Calling Sequence
[x1,p1]=srkf(y,x0,p0,f,h,q,r)
Arguments
- f, h
current system matrices
- q, r
covariance matrices of dynamics and observation noise
- x0, p0
state estimate and error variance at t=0 based on data up to t=-1
- y
current observation Output from the function is
- x1, p1
updated estimate and error covariance at t=1 based on data up to t=0
Description
square root Kalman filter algorithm
Authors
C. B.
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