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Hipparchus-Math · Feb 2, 2025 · 760499c · 760499c
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diff --git a/hipparchus-filtering/src/main/java/org/hipparchus/filtering/kalman/KalmanEstimate.java b/hipparchus-filtering/src/main/java/org/hipparchus/filtering/kalman/KalmanEstimate.java
@@ -18,6 +18,9 @@
 
 import org.hipparchus.linear.RealMatrix;
 
+/** Interface representing a Kalman estimate.
+ * @since 4.0
+ */
 public interface KalmanEstimate {
 
     /** Get the current predicted state.

diff --git a/hipparchus-filtering/src/main/java/org/hipparchus/filtering/kalman/KalmanSmoother.java b/hipparchus-filtering/src/main/java/org/hipparchus/filtering/kalman/KalmanSmoother.java
@@ -31,8 +31,10 @@
  * <p>
  * This implementation is attached to a filter using the observer mechanism.  Once all measurements have been
  * processed by the filter, the smoothing method can be called.
- * </br>
+ * </p>
+ * <p>
  * For example
+ * </p>
  * <pre>{@code
  *     // Kalman filter
  *     final KalmanFilter<SimpleMeasurement> filter = new LinearKalmanFilter<>(decomposer, process, initialState);
@@ -47,7 +49,6 @@
  *     // Smooth backwards
  *     List<ProcessEstimate> smoothedStates = smoother.backwardsSmooth();
  * }</pre>
- * </p>
  *
  * @see "Särkkä, S. Bayesian Filtering and Smoothing. Cambridge 2013"
  */