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MODELLING ESTIMATION AND PREDICTION
8 other sections not shown
adaptive algorithms algebra algorithms Alpha analysis applications assume Assumption asymptotic Beta Bremaud causal filtering components computed consider convergence correlation corresponding covariance matrix criterion defined denote derivative deterministic differential equation discussed distribution DSPP dynamics error example finite frequency Gaussian given Hankel Hankel matrix Hence identification IEEE Trans input interval large deviations least-favorable Lemma loss function Lyapunov equation Markov process martingale mathematical matrix gain methods minimal multistep nonlinear observed obtain operator optimal loss function optimal predictor optimum output point process Poisson process polynomial POV-measure prediction probability proof quantum random variable realization recursive regression relation repeated measurement robust filter satisfies Section sequence Signal Processing sinusoidal solution space spectral measures spectrum state-space stationary statistical Stochastic Approximation stochastic differential equation stochastic process Theorem theory time-varying systems true system uncertainty classes variance white noise zero