Morgan Roger

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In this paper, we present an online identification method to the problem of parameter estimation from binary observations. A recursive identification algorithm with low-storage requirements and computational complexity is derived. We prove the convergence of this method provided that the input signal satisfies a strong mixing property. Some simulation(More)
A new criterion for sequential design of experiments for linear regression model is developed. Considering the information provided by previous collected data is a well-known strategy to decide for the next design point in the case of nonlinear models. The paper applies this strategy for linear models. Besides, the problem is addressed in the context of(More)
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