Download presentation
Presentation is loading. Please wait.
1
Supervised Hebbian Learning
2
Hebb’s Postulate “When an axon of cell A is near enough to excite a cell B and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that A’s efficiency, as one of the cells firing B, is increased.” D. O. Hebb, 1949 A B
3
Linear Associator
4
Hebb Rule
5
Batch Operation
6
Performance Analysis
7
Example
8
Pseudoinverse Rule - (1)
9
Pseudoinverse Rule - (2)
10
Relationship to the Hebb Rule
11
Example
12
Autoassociative Memory
13
Tests
14
Variations of Hebbian Learning
15
MATLAB Neural Network Tool box
17
Batch mode (Train) full propagation
19
On Line (learn) back propagation or incremental
20
Newff
21
Example
22
ADAPT Using [net,Y,E]=adapt(net,P,T) You can find more in neural network tool box
Similar presentations
© 2024 SlidePlayer.com Inc.
All rights reserved.