Perceptron Problem in Neural Network


Research Paper (undergraduate), 2010

11 Pages


Excerpt



NEURAL NETWORK

Perceptron

Dang Xuan Tho

2010

 

Perceptron Problem

Consider a perceptron shown in Fig 9.1. The input data x = [x1,x2]T


Figure 9.1: Perceptron with two-dimensional input data:

- see in printed version -

...

The data x is randomly sample in both classes, and applied to the perceptron. The connection weights are updated following


d (n)= ...

- see in printed version -

The inner product of w and x and an angle θ, shown in Fig. 9.3 between them are related by


- see in printed version -

Figure 9.3: Relation between inner product of two vectors and angle between them

    Please show the regions, where the final weight vector w can locate, in the following two cases. The regions should be indicated by an angle.


a. η is large.
b. η is very small.

And answer some question

1. Obtain the region, where optimum connection weight can locate.
2. Direction of adjustment.

The input potential v can be expressed by


- see in printed version -

 

[....]


1 Schröder, Burkhard + Claudia: Die Online-Durchsuchung, Telepolis, 2008.
2 Vgl. http://www.burks.de/burksblog/category/die-online-durchsuchung, Zugriff: 19.12.09.
3 Zit.: http://www.rbb-online.de/kontraste/beitrag/2007/wanze_im_wohnzimmer.html, Zugriff: 19.12.09.
4 Vgl. http://www.compliancemagazin.de/gesetzestandards/deutschland/bundestagbundesregierung/
deutscherbundestag251007.html, Zugriff: 19.12.09.
5 Vgl. http://www.im.nrw.de/sch/doks/vs/vsg_nrw_2007.pdf, Zugriff: 19.12.09.
6 Vgl, http://juris.bundesgerichtshof.de/cgi-bin/rechtsprechung/document.py?Gericht=bgh&Art=en&Datum=
Aktuell&Sort=12288&anz=562&pos=3&nr=38775&linked=pm&Blank=1, Zugriff: 19.12.09

Excerpt out of 11 pages

Details

Title
Perceptron Problem in Neural Network
Author
Year
2010
Pages
11
Catalog Number
V153037
ISBN (eBook)
9783640648870
ISBN (Book)
9783640648955
File size
395 KB
Language
English
Tags
Perceptron, Problem, Neural, Network
Quote paper
Dang Xuan Tho (Author), 2010, Perceptron Problem in Neural Network, Munich, GRIN Verlag, https://www.grin.com/document/153037

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