16.322 Stochastic Estimation and Control
Estimation and control of dynamic systems. Brief review of probability and random variables. Classical and state-space descriptions of random processes and their propagation through linear systems. Frequency domain design of filters and compensators. The Kalman filter to estimate the states of dynamic systems. Conditions for stability of the filter equations.
16.322 will be offered this semester (Fall 2018). It is instructed by N. Roy.
This class counts for a total of 12 credits. This is a graduate-level class.
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