Advances in Statistical Signal Processing, Volume 1H. Vincent Poor |
Contents
Chapter 3 | 24 |
MODELLING ESTIMATION AND PREDICTION | 53 |
MATHEMATICS | 119 |
Copyright | |
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A₁ algebra algorithms analysis applications assume Assumption asymptotic B₁ Brémaud causal filtering components computed condition consider convergence corresponding covariance matrix criterion defined denote deterministic differential equation distribution dynamics error estimate example finite frequency G₁ Gaussian given Hankel Hankel matrix identification IEEE Trans input large deviations least-favorable Lemma linear loss function Lyapunov equation Markov process martingale mathematical methods minimal Model Order multistep N₁ nonlinear observed obtain optimal loss function optimal predictor output P₁ parameters point process Poisson process polynomial POV-measure prediction probability problem proof quantum random variable realization recursive regression robust filter satisfies Section sequence Signal Processing sinusoidal solution space spectral measures spectrum statistical Stochastic Approximation stochastic differential equation stochastic process T₁ Theorem theory time-varying systems true system vector white noise X₁ y₁ zero