Can anyone recommend a website or give me a brief of how backpropagation is implemented in a NN? I understand the basic concept, but I'm unsure of how to go about writing the code. Many of sources I've found simply show equations without giving any explanation of why they're doing it, and the variable names make it difficult to find out...
I understand the way how the neural net is working, but if I want it to use for image processing, actually character recognition, I can't understand, how can I input the image data to the neural net, if I can have a very big image of an A letter! May be I should try to get some info from the image, some specifications of the image, and ...
I'm looking for ideas for a Neural Networks project that I could complete in about a month or so. I'm doing it for the National Science Fair, so I need something that has some curb appeal as well since it's being judged. It doesn't necessarily have to be completely new and unique, I'm just looking for ideas, but it should be complex eno...
I'm quite new with this topic so any help would be great. What i need is to optimize a neural network in MATLAB by using GA. My network has [2x98] input and [1x98] target, i've tried consulting matlab help but im still kind of clueless about what to do :( so, any help would be appreciated. Thanks in advance. edit: i guess i didn't say w...
Would someone be able to explain to me or point me to some resources of why (or situations where) more than one hidden layer would be necessary or useful in a neural network? ...
I'm starting neural networks, currently following mostly D. Kriesel's tutorial. Right off the beginning it introduces at least three (different?) learning rules (Hebbian, delta rule, backpropagation) concerning supervised learning. I might be missing something, but if the goal is merely to minimize the error, why not just apply gradient...
I was wondering if you creative minds out there could think of some situations or applications in the web environment where Neural Networks would be suitable or an interesting spin. Edit: Some great ideas here. I was thinking more web centric. Maybe bot detectors or AI in games. ...
Backpropagation calculates dW (weight delta) per weight per pattern, so it's straightforward how to modify weights when doing stochastic training. How do I use it for batch training, though? Simply accumluate dW over the entire training set and then apply the modfication, or is there more to it? ...
The need for having part of the training set used as verification data is straightforward, but I am not really clear on how and at what stage of the training should it be incoperated? Is it at the end of the training (after reaching a good minimum for the training data)? If so, what should be done if the verification data yeilds a big e...
I am trying to use ANN for pitch detection of musical notes. The network is a simple two-layer MLP, whose inputs are basically a DFT (averaged and logarithmically distributed), and 12 outputs correspond to the 12 notes of a particular octave. The network is trained with several samples of those 12 notes played by some instrument (one no...
When designing a feed forward neural network with multiple outputs, is there a conceptual difference (other than computational efficency) between having a single network with multiple outputs, and having multiple networks, each having a single output? Although output neurons in the same network don't affect each other "on the fly", they...
I have seen a few times people using -1 as opposed to 0 when working with neural networks for the input data. How is this better and does it effect any of the mathematics to implement it? Edit: Using feedforward and back prop Edit 2: I gave it a go but the network stopped learning so I assume the maths would have to change somewhere? ...
To learn FPGA programming, I plan to code up a simple Neural Network in FPGA (since it's massively parallel; it's one of the few things where an FPGA implementation might have a chance of being faster than a CPU implementation). Though I'm familiar with C programming (10+ years). I'm not so sure with FPGA development stuff. Can you prov...
Update: a better formulation of the issue. I'm trying to understand the backpropagation algorithm with an XOR neural network as an example. For this case there are 2 input neurons + 1 bias, 2 neurons in the hidden layer + 1 bias, and 1 output neuron. A B A XOR B 1 1 -1 1 -1 1 -1 1 1 -1 -1 -1 I'm using the...
I need to try a Neural Network on an interesting research problem I'm faced with. Any language is fine, although I suspect the best NN's are probably in C. I would like to be able to integrate with Java or PHP, but it's not 100% necessary. What is the best choice from the dozens of open-source NN frameworks out there? ...
Could you give a sample of NN ? I mean something like implemented ORC but easier. And could you explain how does it work but on samples? ...
I am trying to write a program for weather forecasting using backpropagation. I am a beginner in this field. I have historical data with different parameters like temperature, humidity, wind speed, rainfall etc. I am confused about how to provide this data to the input layer. Is each input node to be given the whole of the data for a g...
Does anybody know of an (open source) implementation of Liquid State Machines? ...
I'm looking for a good (and, if possible, simple) open-source Python library to do neural network computations. It should be able to deal with multiple-layer networks and backpropagation learning. Speed of implementation does not really matter for me. Does anyone have suggestion on what I can use? Thanks ...
Seeing that as as far as we know, one half of your brain is logical and the other half of your brain is emotional, and that the wants of the emotional side are fed to the logical side in order to fulfill those wants; has there been any research done in connecting two separate neural networks to one another (one trained to be emotional, ...