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hipparchus-filtering/src/main/java/org/hipparchus/filtering/kalman/KalmanEstimate.java

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import org.hipparchus.linear.RealMatrix;
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/** Interface representing a Kalman estimate.
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* @since 4.0
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*/
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public interface KalmanEstimate {
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/** Get the current predicted state.

hipparchus-filtering/src/main/java/org/hipparchus/filtering/kalman/KalmanSmoother.java

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* <p>
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* This implementation is attached to a filter using the observer mechanism. Once all measurements have been
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* processed by the filter, the smoothing method can be called.
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* </br>
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* </p>
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* <p>
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* For example
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* </p>
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* <pre>{@code
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* // Kalman filter
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* final KalmanFilter<SimpleMeasurement> filter = new LinearKalmanFilter<>(decomposer, process, initialState);
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* // Smooth backwards
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* List<ProcessEstimate> smoothedStates = smoother.backwardsSmooth();
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* }</pre>
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* </p>
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*
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* @see "Särkkä, S. Bayesian Filtering and Smoothing. Cambridge 2013"
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*/

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