diff --git a/15_Adaptive_Filtering/Adaptive_Filtering.ipynb b/15_Adaptive_Filtering/Adaptive_Filtering.ipynb
index c6a1ff0..d337134 100644
--- a/15_Adaptive_Filtering/Adaptive_Filtering.ipynb
+++ b/15_Adaptive_Filtering/Adaptive_Filtering.ipynb
@@ -1,7 +1,7 @@
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+  "signature": "sha256:97b2f171dee324b433a935a17ca3a82b43169f655f4090827fc6587dbce6f8fe"
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@@ -1276,7 +1276,7 @@
       "\n",
       "The fading memory filter accounts for this problem by giving less weight to older measurements, and greater weight to the more recent measurements. \n",
       "\n",
-      "There are many formulations for the fading memory Filter; I use the one provided by Dan simon in *Optimal State Estimation* [3]. I will not go through his derivation, but only provide the results.\n",
+      "There are many formulations for the fading memory Filter; I use the one provided by Dan Simon in *Optimal State Estimation* [3]. I will not go through his derivation, but only provide the results.\n",
       "\n",
       "The Kalman filter equation for the covariances of the estimation error is\n",
       "\n",