diff --git a/doc/Messprotokoll.md b/doc/Messprotokoll.md
index 17cad8b..0ebed37 100644
--- a/doc/Messprotokoll.md
+++ b/doc/Messprotokoll.md
@@ -1,4 +1,4 @@
-# CPP-NLMS-Testreihe
+# 1. CPP-NLMS-Testreihe
 #### Paramter: 
 				- Input: 500.000 Pixel (-n 500000)
 				- WindowSize: 5 (Standart Value)
@@ -7,7 +7,7 @@
 				- random seed generator : 3 (-s 3)
 
 
-## 1. Local Mean
+### 1. Local Mean
 
 Lernrate	|	meanerror	|	devitation
 ---	|	---	|	---
@@ -22,7 +22,7 @@ Lernrate	|	meanerror	|	devitation
 0.9	|	0.174440|	8171.260237
 1.0	|	0.196529|	10057.264574
 
-## 2. direct Predecessor
+### 2. direct Predecessor
 
 Lernrate	|	meanerror	|	devitation
 ---	|	---	|	---
@@ -37,7 +37,7 @@ Lernrate	|	meanerror	|	devitation
 0.9	|	-7547134082896249132941312.000000|	3877153348329978955993364733716443880442465820831329026048.000000
 1.0	|	3761239144093188417284117395383469067145028584884793393044299775046771047758036992.000000|	2074572983654522674987602010560539857768301297996124872466118751856211301657828168212459204392861396853691477732320683100737172969672730282637731961860360049654132492992512.000000
 
-## 3. differential Predecessor
+### 3. differential Predecessor
 
 Lernrate	|	meanerror	|	devitation
 ---	|	---	|	---
@@ -51,3 +51,61 @@ Lernrate	|	meanerror	|	devitation
 0.8	|	0.013732|	1363.663734
 0.9	|	-0.071016|	4623896.100036	
 1.0	|	-211924.365595|	556770831730198528.000000
+
+___
+
+# 2. CS-NLMS-Testreihe
+#### Parameter:
+				-N:4000 Pixel
+				-M: 5
+				-Learnrate: 0.1 bis 1.0 (increased by 0.1)
+				-Image: boats.y.png
+				--> Gewichte sind random, daher nicht reproduzierbar!
+
+
+### 1. local mean
+
+Lernrate	|	Average error	|	Variance of the error
+---	|	---	|	---
+0.1	|	-0,0223811013862385|	5337,82462718957
+0.2	|	-0,0622259728578006|	7363,56898611733
+0.3	|	-0,0298976210637875|	9614,92806843726
+0.4	|	0,0849844894447272|	12088,2433018213
+0.5	|	0,299055989866592|	14819,6805234785
+0.6	|	0,585283074155977|	17874,0914703503
+0.7	|	0,979106442634296|	21337,9978781998
+0.8	|	1,46391408202542|	25322,8680485397
+0.9	|	2,05872807071837|	29964,9719994441
+1,0	|	2,79656379441662|	35436,9340804565
+
+### 2. direct predecessor
+
+Lernrate	|	Average error	|	Variance of the error
+---	|	---	|	---
+0.1	|	0,151005103097187|	5471,5876773699
+0.2	|	0,606943328690361|	7729,18121268243
+0.3	|	1,14390553779214|	10465,2060324616
+0.4	|	1,76810718228813|	13695,8876087231
+0.5	|	2,5193083296817|	17431,0433982945
+0.6	|	3,38144695588288|	21696,5188824818
+0.7	|	4,36367842697108|	26566,2513099756
+0.8	|	5,51257464442153|	32193,8755290981
+0.9	|	6,83374986915135|	38850,115776936
+1.0	|	8,38129514988831|	46958,0983013679
+
+### 3. differential predecessor
+
+Lernrate	|	Average error	|	Variance of the error
+---	|	---	|	---
+0.1	|	-0,0160622191672049|	4750,33040669542
+0.2	|	0,00640864710641419|	6041,46065665648
+0.3	|	0,0432263456982662|	7412,09833871273
+0.4	|	0,106075295986603|	8891,97578539296
+0.5	|	0,174689052473554|	10532,273473301
+0.6	|	0,241331954473674|	12394,8177286223
+0.7	|	0,359973579958283|	14552,6708886431
+0.8	|	0,494261683495002|	17102,3682973733
+0.9	|	0,671346960651145	|	20166,0023256068
+1.0	|	0,892045554010017|	23907,2852270274
+
+