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Similarities and differences between the algorithms based on the Bayesian approach, commonly used for solution of nonlinear navigation estimation problems, and the algorithms based on neural networks (NN) are analyzed. The possibilities of using NN for solution of nonlinear navigation problems are discussed.
This paper presents a sequential estimation procedure for the unknown parameters of a continuous-time stochastic linear regression process. As an example, the sequential estimation problem of two dynamic parameters in stochastic linear systems with memory and in autoregressive processes is solved. The estimation procedure is based on the least squares method with weights and yields estimators with...
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