A normalized lattice algorithm for AR spectral analysis and system identification filters with symmetric impulse response
A time-recursive normalized lattice algorithm is derived for the least-squares (LS) estimation of the unknown parameters of an FIR (finite impulse response) filter with symmetric impulse response. A byproduct is an algorithm for the LS estimation of the unit step backward predictor of the input time series, based on the simultaneous minimization of the forward and backward total squared error power, which has successfully been used in the maximum-entropy spectral analysis (MESA) method. >