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# 1. CPP-NLMS-Testreihe
## 1.1 Veränderung der Lernrate
#### Paramter:
- Input: 500.000 Pixel (-n 500000)
- WindowSize: 5 (Standard Value)
- WindowSize: 5 (Standart Value)
- Lernrate von 0.1 bis 1.0 (increased by 0.1)
- -i cathedral.ppm
- random seed generator : 3 (-s 3)
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### 1. Local Mean
Lernrate | meanerror | devitation
--- | --- | ---
0.1 | 0.017622| 264.808714
0.2 | 0.035715| 563.756509
0.3 | 0.054145| 1058.390726
0.4 | 0.072960| 1749.137624
0.5 | 0.092207| 2636.592222
0.6 | 0.111931| 3721.514220
0.7 | 0.132180| 5004.829359
0.8 | 0.153002| 6487.641093
0.9 | 0.174440| 8171.260237
1.0 | 0.196529| 10057.264574
Lernrate | meanerror | variance
--- | --- | ---
0.1 | 0.020861| 373.760784
0.2 | -0.015231| 1261.386282
0.3 | -0.054507| 2574.244199
0.4 | -0.088173| 4229.104809
0.5 | -0.116079 | 6169.762185
0.6 | -0.139313 | 8360.777760
0.7 | -0.158889 | 10783.351638
0.8 | -0.175600 | 13432.957565
0.9 | -0.190101 | 16318.529330
1.0 | -0.202958 | 19463.062580
### 2. direct Predecessor
Lernrate | meanerror | devitation
--- | --- | ---
0.1 | 0.034605| 1165.639836
0.2 | 0.061290| 5143.795751
0.3 | 0.081941| 14101.954880
0.4 | 0.098059| 33151.61923
0.5 | 0.111109| 73575.962146
0.6 | 0.123070| 159449.145873
0.7 | 0.138492| 347221.927325
0.8 | 519.742508| 8159987385389.823242
0.9 | -7547134082896249132941312.000000| 3877153348329978955993364733716443880442465820831329026048.000000
1.0 | 3761239144093188417284117395383469067145028584884793393044299775046771047758036992.000000| 2074572983654522674987602010560539857768301297996124872466118751856211301657828168212459204392861396853691477732320683100737172969672730282637731961860360049654132492992512.000000
0.1 | 0.024560 | 608.448633
0.2 | -0.030306 | 2007.513911
0.3 | -0.084634 | 3959.201147
0.4 | -0.126798 | 6328.009325
0.5 | -0.157719 | 9057.241991
0.6 | -0.179736 | 12137.852301
0.7 | -0.194805 | 15592.808948
0.8 | -0.204488 | 19471.279015
0.9 | -0.210085 | 23849.267714
1.0 | -0.212681 | 28835.466521
### 3. differential Predecessor
Lernrate | meanerror | devitation
--- | --- | ---
0.1 | 0.002158| 35.172878
0.2 | 0.003306| 33.315664
0.3 | 0.003656| 32.549577
0.4 | 0.003311| 33.097449
0.5 | 0.002340| 35.717416
0.6 | 0.000869| 43.040214
0.7 | -0.000213| 71.249809
0.8 | 0.013732| 1363.663734
0.9 | -0.071016| 4623896.100036
1.0 | -211924.365595| 556770831730198528.000000
0.1 | 0.046246 | 237.604268
0.2 | 0.058362 | 838.182243
0.3 | 0.060553 | 1834.829054
0.4 | 0.060390 | 3227.671286
0.5 | 0.060858 | 5016.829374
0.6 | 0.063120 | 7202.687465
0.7 | 0.067694 | 9785.843689
0.8 | 0.074840 | 12767.049840
0.9 | 0.084710 | 16147.248088
1.0 | 0.097443 | 19927.694764
### 4. NLMS
Lernrate | meanerror | devitation
--- | --- | ---
0.1 | -0.865235 | 51.897994
0.2 | -0.916315 | 67.761425
0.3 | -0.950006 | 82.291526
0.4 | -0.975096 | 96.554001
0.5 | -0.995089 | 111.236008
0.6 | -1.011618 | 126.820482
0.7 | -1.025538 | 143.713619
0.8 | -1.037385 | 162.334219
0.9 | -1.047550 | 183.192878
1.0 | -1.056358 | 206.993456
## 1.2 Veränderung der WindowSize
#### Paramter:
- Input: 500.000 Pixel (-n 500000)
- WindowSize: -w {1,3,5, 8, 10, 15, 20, 25, 50, 100}
- Lernrate: -l 0.6
- -i cathedral.ppm
- random seed generator : 3 (-s 3)
>Tabelle beinhaltet jeweils den 'mean error' der jeweiligen Variante
| Windowsize | local Mean | direct Predecessor | differential Predecessor | NLMS |
|---|---|---|---|---|
| 1 | 0.330125 | 0.330131 | 0.330131 | -1.063652 |
| 3 | 0.444605 | 0.412069 | 0.413190 | -1.089547 |
| 5 | -0.139313 | -0.179736 | 0.063120 | -1.011618 |
| 8 | 0.181180 | 0.042986 | 0.221078 | -0.873373 |
| 10 | 0.279242 | 0.188497 | 0.291145 | -0.811906 |
| 15 | 0.215564 | 0.222018 | 0.265400 | -0.696719 |
| 20 | 0.273161 | 0.383155 | 0.194116 | -0.615447 |
| 25 | 0.213731 | 0.276315 | 0.185892 | -0.576340 |
| 50 | 0.467920 | 0.463972 | 0.188099 | -0.479407 |
| 100 | -0.331102 | -0.412149 | -0.018204 | -0.506369 |
___
# 2. CS-NLMS-Testreihe
#### Parameter:
-N:4000 Pixel