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
- 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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