lets deal with neural networks

narayana murthy · 2011-07-16T04:46:32+00:00

hey friends, i never noticed a thread about neural networks in this CE from my existence so i am taking initiation as it is a very useful and research topic ofcourse i am interested because it is included in my syllabus now i am stating with a small question what is neural network and what all CEan's are thinking about brain?? i am giving a time of 20hours for all the interested ceans to answer later i will give the answer

PraveenKumar Purushothaman

@praveenkumar-66Ze92 • Jul 16, 2011

I am interested but I have no idea about it... 😔

0

Ankita Katdare

@abrakadabra • Jul 16, 2011

I think we can all learn a lot from this thread.
Where to start?

0

Adivy

@adivy-4HW5my • Jul 16, 2011

Neural networks are computational models inspired by the real neurons.
There are over 100 billion neurons in our brain.Ofcourse everyone must have heard about neurons but have you ever thought of what makes them different from other cells??Why are they so important?(I know some of you may know the answer but still).
There are two things that make them different:-
Firstly their special structure i.e that is apart from normal cell components they have these dendrites(number of arms you can say ).
Secondly they are electrically active.
Neurons have resting as well as active states.They connect to other neurons via joints called Synapse.It is like a neuron with its dendrites connected to dendrites of other neurons at synapses.
This was all biology stuff.So coming to how we can model it,its like simply capturing the behaviour of a neuron into mathematical model.
This mathematical model is called McCulloch-Pitts Model.Its is like a circle representing a neuron with inputs x1,x2,..xi,..,xn which are the information coming from different dendrites of the neuron and an output y which is a function of inputs with their weights(w).So the equation is somewhat like this:-
y=g((summation of wi*xi)-b )
Neural netwotk(NN) is a parametric model that can model arbitrary i/o relationships.It can learn i/o relationships from sample data.
Applications of NN in which i was interested was Optical character recognition(OCR) which is basically a DSP application.There are many more applications like in VLSI,contol &instrumentation,etc.
There are varieties of NN:-
Multilayer Perceptions/Backpropagation networks,
Radial Basis Function Networks (I know only this one because it was involved in OCR),
Hopfield network,Recurrent networks,Modular networks etc.

Guys this is what i know about neural networks.I didnt particularly study this as a subject but i have used it in studyin or doing some OCR techniques.Any mistakes please do correct me.

0

Ankita Katdare

@abrakadabra • Jul 16, 2011

@Adivy: That was enlightening! 😀
What are the other major applications of neural networks?

0

Adivy

@adivy-4HW5my • Jul 16, 2011

@Abrakadabra:😀 Like I said it was a very little part of what I studied in DSP Application,so I just shared what I knew.I dont have deep knowledge on the topic.And about the application there are many like:-
Pattern recognition or identifying patterns or trends in data(One of the main apps),
Robotics,detection and tracking of moving items ,motion detection ,etc
Its widely used in Artificial intelligence.
What is interesting is their ability to learn by example unlike conventional computers which are algorithmic.
So we can say NN=Learning by example😀Like how we grow up taking others as example.

Replies