This text focuses on linear stochastic models, whose theoretical foundations are the most fully worked out and the most frequently applied area of systems and control theory. Presents a unified and mathematically rigorous exposition of the main results of the theory of linear discrete-time-parameter stochastic systems. Begins with a thorough examination of the fundamentals of stochastic processes and the construction of stochastic systems, and goes on to provide an integrated treatment of the theories of prediction, regulation, modeling and estimation of system dynamics (system identification), and control. Text concludes with a presentation of stochastic adaptive control theory. Coverage of all topics incorporates the most recent research in the field.
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