+ All Categories
Home > Documents > Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Date post: 14-Dec-2015
Category:
Upload: allyson-ridgely
View: 217 times
Download: 2 times
Share this document with a friend
Popular Tags:
42
Hopefully a clearer version of Neural Network
Transcript
Page 1: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Hopefully a clearer version of Neural Network

Page 2: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

I1

O2

O1H1

H2I2

Page 3: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Layers of Weights

• We Name Sets of Weights between layersAs W1 for weights between input Layer and

First Hidden LayerW2 for weights between next 2 layers and WN-1 for Weights between N-1th and Nth

Layer(i.e. Output Layer)In our example Net we just have 3 layersInput Hidden and Output So we have just

W1 and W2

Page 4: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

I1

O2

O1H1

H2I2

W1W2

Page 5: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Weights along Individual Links

• Convention

• Each Weight is named as follows

• WNij

• N refers to the Layer of Weights

• So Between Input and First Hiden Layer i.e. W2ij is the Reference

• Between Hidden and Output W2ij

Page 6: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Individual Weights within a layer

• Reference WNij

• WN refers to the Weight Layer

• ij refers to the indices of the source and destination nodes.

• So for example the weight between hidden node h1 and output node o2

• It belongs to weight layer 2 so W2

• i = 1 and j = 2 so Weight is W212

Page 7: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

I1

O2

O1H1

H2I2

W1W2

W212

Page 8: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Full Naming of Weight Set

Page 9: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

I1

O2

O1H1

H2I2

W1 W2

W212W112

W221

W211

W222

W121

W111

W122

Page 10: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

With Actual Weights

Page 11: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

I1

O2

O1H1

H2I2

W1 W2

0-1

0

-1

-1

0

1

1

Page 12: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Inputs

• 1 and 0

• Target outputs {0.7,0.6}

Page 13: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

I1

O2

O1H1

H2I2

W1 W2

0-1

0

-1

-1

0

1

1

1

0

Page 14: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Hidden Layer Computation

• Xi =iW1 = • 1 * 1 + 0 * -1 = 1, • 1 * -1 + 0 * 1 = -1 = • { 1 - 1} = {Xi1,Xi2} = Xi

xF

1

1

Page 15: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

• h = F(X)• h1 = F(Xi1) = F(1)• h2 = F(Xi2) = F(-1)

27.01

1

1

1)2(

73.01

1

1

1)1(

)1(2

)1(1

xi

xi

XiF

XiF

Page 16: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

I1

O2

O1H1

H2I2

W1 W2

0-1

0

-1

-1

0

1

1

1

0

0.73

0.27

Page 17: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Next Outputs

Page 18: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Output Layer Computation

• X = hW2 = • 0.73 * -1 + 0.27 * 0 = -0.73, • 0.73 * 0 + 0.27 * -1 = -0.27 =• { -0.73 - 0.27} = {X1,X2} = X

xF

1

1

Page 19: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

• O = F(X)• O1 = F(X1)• O2 = F(X2)

433.01

1

1

1)2(

325.01

1

1

1)1(

)27.0(2

)73.0(1

x

x

XF

XF

Page 20: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

I1

O2

O1H1

H2I2

W1 W2

0-1

0

-1

-1

0

1

1

1

0

0.73

0.27

0.325

0.433

Page 21: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Error

• D= Output(1 – Output)(Target – Output)• Target T1 = 0.7 , O1 = 0.325 = 0.33

• d1 = 0.33( 1 -0.33)(0.7 -0.33 ) = 0.33 (0.67)(0.37) = 0.082

• Target T2 = 0.6 , O2 = 0.433 = 0.43

• d2 = 0.43(1 - 0.43)(0.6-0.43) = 0.43(0.57)(0.17) = 0.42

Page 22: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Weight Adjustment

• △W2t = α hd + Θ △W2t-1

• where α = 1• Time t = 1 so no previous time

2212

211121

2

1

dhdh

dhdhdd

h

hhd

)042.0*27.0()082.0*27.0(

)042.0*73.0()082.0*73.0(042.0082.0

27.0

73.0hd

Page 23: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Weight Adjustments

)012.0()022.0(

)031.0()06.0(

Page 24: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Weight Change

)012.02()22.02(

)031.02()06.02(

2221

1211

WW

WW

Page 25: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Equals

)012.01()022.00(

)031.00()06.01(

Page 26: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Equals

)988.0()022.0(

)031.0()94.0(

Page 27: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Putting these new weights in the diagram

• To get

Page 28: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

I1

O2

O1H1

H2I2

W1 W2

0.031-1

0.022

-0.94

-0.988

0

1

1

Page 29: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Next

• Calculate Change on W1 layer weights

Page 30: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Error Calculatione = h(1 - h)W2d

21

11

h

h

2

1

d

d

2221

1211

22

22

WW

WW 21 hh

2

1

e

e

Page 31: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Another Way to write the error

outputsk

kikiih dWhhe )1(

Page 32: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

What is this

• Outputs are O1 and O2

• So k = {1,2}• So if i = 1

outputsk

kikdW

summation

Page 33: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

2121112,1,1

dWdWdWdWki

kikoutputsk

kik

Page 34: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

I1

O2

O1H1

H2I2

W1 W2

0.031-1

0.022

-0.94

-0.988

0

1

1

Page 35: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

This equals

• e1 = (h1(1-h1)W11 D1 +W12D2• e2 = (h2(1-h2)) W21 D1 +W22D2• d1 = 0.082 d2 = = 0.042e1 = (0.73(1-0.73))( -1* 0.082 +0*0.042)• e2 =( 0.27(1-0.27)) (0 *0.082 +-1*0.042)

• e1 = (0.73(0.27)( -0.082))• e2 =( 0.27(0.73)) (-0.042)• e1 = -0.016• e2 = -0.0083

Page 36: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Weight Adjustment

• △W1t = α Ie + Θ △W2t-1

• where α = 1

2212

211121

2

1

eIeI

eIeIee

I

IIe

)0083.0*0()016.0*0(

)0083.0*1()016.0*1(0083.0016.0

0

1Ie

Page 37: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Weight Adjustment

)0()0(

)0083.0()016.0(

Page 38: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Existing W1

10

11

11

11

2221

1211

WW

WW

Page 39: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

Weight Change W1

)01()0(

)0083.01()016.01(

Page 40: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

New W1

10

0083.1884.0

Page 41: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

• Changing Net

Page 42: Hopefully a clearer version of Neural Network. I1 O2 O1 H1 H2I2.

I1

O2

O1H1

H2I2

W1 W2

-0.102-1.0083

-0.04

-1.109

-1.038

0

0.884

1


Recommended