@@ -30,7 +30,7 @@ For a linear-quadratic dynamic programming problem, the idea involves these step
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33 | | -## Undiscounted dynamic programming problem |
| 33 | +## Undiscounted Dynamic Programming Problem |
34 | 34 | |
35 | 35 | Here is a nonstochastic undiscounted LQ dynamic programming with cross products between |
36 | 36 | states and controls in the objective function. |
@@ -89,7 +89,7 @@ F & = F^* + Q^{-1} H.
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90 | 90 | +++ |
91 | 91 | |
92 | | -## Kalman filter |
| 92 | +## Kalman Filter |
93 | 93 | |
94 | 94 | The **duality** that prevails between a linear-quadratic optimal control and a Kalman filtering problem means that there is an analogous transformation that allows us to transform a Kalman filtering problem |
95 | 95 | with non-zero covariance matrix between between shocks to states and shocks to measurements to an equivalent Kalman filtering problem with zero covariance between shocks to states and measurments. |
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