Adaptive Input Estimation
IFAC Symposium ACASP 89: Adaptive
Systems in Control and Signal Processing,
Glasgow, UK, pp 631-636, April 1989.
The paper studies the problem of estimating the input signal
to a scalar discrete-time linear system
The system is known, while the noise
and input spectra are unknown. (This problem differs from
that of blind deconvolution, where the system is unknown.)
An adaptive algorithm for estimating the input to a linear system
is presented. This explicit self-tuning filter is based on the
identification of an ARMA innovations model. From that model,
input and measurement noise descriptions
Main tools in the algorithm are the solution of two
linear systems of equations.
The basic algorithm can be used for input signals
described by ARMA models and moving average
An extension of the algorithm involves the use of
on-line model reduction and spectral factorization.
Simulation experiments illustrate the filtering performance.
- Related publications:
in IEEE Trans. ASSP 1989 on the design of linear scalar
Later Conference paper
in SPIE'91 on adaptive deconvolution.
Paper in Automatica 1990,
where the identifiability conditions are derived.