Comments for Neural Networks

Comment on Can someone help explain Neural Networking in simple terms? by Jon

Jon — Tue, 09 Feb 2010 08:38:59 +0000

Here is a web page that covers it better than the wikipedia article:

http://www.ai-junkie.com/ann/evolved/nnt1.html
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Comment on Can someone help explain Neural Networking in simple terms? by Veronicow

Veronicow — Tue, 09 Feb 2010 08:23:59 +0000

I’m in a "show them where to find their answers and save yourself some typing" mood today and I’m sorry if as a fourth year you actually though to do this first, but…

The internet is good.
Google is your friend.
Wikipedia is Decent…ish.

http://en.wikipedia.org/wiki/Neural_network
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Bsc Computer science

Comment on i want to built a model reference controller with neural networks principle for my thesis n i need help on it? by God answers all questions

God answers all questions — Sat, 16 Jan 2010 05:02:59 +0000

This is the message we have heard from him and proclaim to you, that God is light and in him is no darkness at all.
If we say we have fellowship with him while we walk in darkness, we lie and do not live according to the truth;
but if we walk in the light, as he is in the light, we have fellowship with one another, and the blood of Jesus his Son cleanses us from all sin.
If we say we have no sin, we deceive ourselves, and the truth is not in us.
If we confess our sins, he is faithful and just, and will forgive our sins and cleanse us from all unrighteousness.
If we say we have not sinned, we make him a liar, and his word is not in us.
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Comment on In neural networks how would you answer the following? by Wally

Wally — Tue, 12 Jan 2010 13:11:59 +0000

Probably when w -> 0
exp(-w) -> 1
and 1/(1 + exp(-w)) -> 1/2
Hope this helps
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Comment on Optical Neural Networks? by George

George — Sat, 09 Jan 2010 09:38:59 +0000

http://www.sciencedirect.com/science?_ob=ArticleListURL&_method=tag&_temp=&sort=r&sisrterm=&_ArticleListID=932866142&view=c&_chunk=0&count=1000&_st=&refsource=&_acct=C000017279&_version=1&_urlVersion=0&_userid=333848&md5=131b998d1b91f78af5e069e4c4945a08

have a search through that list of 19259 papers, 90% are free to download

good luck
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Comment on i need an video tutorials on neural networks where do i get ? by suraj

suraj — Wed, 06 Jan 2010 07:07:59 +0000

I THINK http://www.youtube.com OR http://www.expertvillage.com ARE THE BEST WEBSITES FOR YOU…..
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Comment on Can I study Neural networks&artificial intelligence technology at Mtech if i have Biomedical engineering at BE? by scottsdalehigh64

scottsdalehigh64 — Sat, 02 Jan 2010 19:37:59 +0000

Certainly you can if you have the prerequisites. However, I would stick with biomedical engineering. It has more practical applications.
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I have studied artificial intelligence, and I was a biomedical engineering fellow at Johns Hopkins Medical School.

Comment on doubts regarding face recognition using artificial neural networks? by nanren888

nanren888 — Wed, 30 Dec 2009 22:02:59 +0000

Sorry, don’t get "Olivia O"’s answer.

NN are not really my field, but I’ll answer part of it.

The thing about tasks such as face recognition is that they are difficult supervised learning. Supervised means that you know the answers for some inputs & can train on them.

Pixel by pixel is usually a problem for such tasks as when you change the lighting or face angle, the pixels change. What you might like instead is to extract.process the data (pixels?) into some other features, like the separation of eyes, length of nose, scar on cheek, whatever, you don;t really care as long as they are essentially invariant over the things that change & constant for the same faces.

Therefore feature selection is an issue.

NN usually have internal layers between neurons. These layers represent features developed internally during training & you do not necessarily care what the feature is, just that it makes the correct decision.

A NN therefore is a way to implement a trainable feature selector & decision mechanism.
There are likely disagreements between those who like NN & others, but I read it explained once that NN tend to be black box: They will train & achieve a level of performance but you cannot easily determine how they are making the decision.
In contrast support vector machines can easily show you how the decision is made.

NN can be created to represent many traditional adaptive algorithms & hence often in many ways are just the implementation of an algorithm that likely existing in other implementation before NNs.

The other thing about storing databases, is that most images have a LOT of pixels. To store & then calculate & make decisions based on all of them can be a problem: imaging Google sifting millions of images to answer a query. Instead the idea of calculating & storing a smaller set of features is attractive for storage & speed. That is you have reduced the dimensionality of the problem.
Hope this helps. Maybe someone who is an expert can correct my gross simplifications & errors.
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Comment on what design control system to dc motor with Artificial Neural Networks? by Simon R

Simon R — Fri, 25 Dec 2009 18:23:59 +0000

I could answer this if there were a sentence constructed in English grammar. Neural nets are learning engines and could be trained to control a motor in response to complex stimuli.
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Comment on what are the problems that can be optimized using neural networks.? by Nahee_Enterprises

Nahee_Enterprises — Tue, 15 Sep 2009 16:25:59 +0000

You did not state whether you were referring to Biological (the traditional meaning) or to Artificial (the modern usage). For further reading, try this link: http://en.wikipedia.org/wiki/Neural_network

It also makes a difference in the types of problems being optimized when referring to either of these definitions of a neural network. And to exactly what conditions need to be met to classify something as being optimized.

Your question and follow-up sentence are much to vague to be fully answered within the confines of Yahoo Answers. They produce more questions about further details than has been provided.

Try doing a Google search using the following keywords:

neural networks optimized problem solving

You should be able to get several links such as these:

http://www.springerlink.com/content/0q4443xhu753237r/
http://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/cs11/report.html
http://www2.computer.org/portal/web/csdl/doi/10.1109/PDCAT.2005.13

.
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