Online quantization in nonlinear filtering
نویسندگان
چکیده
Sequential Baysian filtering arises in many practical problems. The complexity of this problem depends very much on the underlying mathematical model. When a linear Gaussian model is assumed, the well known Kalman filter provides the desired optimal solution. However, in many situations these assumptions do not hold, even approximately. We consider here a somewhat simplified version of the general set up. Namely, we have the following state space model
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