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Focusing on the problem of the input and output data both contain measurement noise in linear time invariant system, this paper proposes that utilizing Tikhonov regularization of total least squares to solve the ill-poseness in process of adaptive dynamic programming. By applying the presented algorithm, the designed controller is obtained through the input and output data of the system, i.e. the...
This paper introduces an approach to estimate the true states for stochastic Boolean dynamic system (SBDS), where the state evolution is governed by Boolean functions with additive binary process noise while the measurement is an arbitrary function of the state yet with additive binary measurement noise. The problem of figuring out the true state using the only available noisy outputs is crucial for...
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