A community portal about Neural networks with blogs, videos, and photos. According to Wikipedia.org: A neural network is a computing paradigm that is loosely modeled after cortical structures of the brain. It consists of interconnected...
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A community portal about Neural networks with blogs, videos, and photos. According to Wikipedia.org: A neural network is a computing paradigm that is loosely modeled after cortical structures of the brain. It consists of interconnected processing elements called neurons that work together to produce an output function. The output of a neural network relies on the cooperation of the individual neurons within the network to operate. Processing of information by neural networks is often done in parallel rather than in series. Since it relies on its member neurons collectively to perform its function, a unique property of a neural network is that it can still perform its overall function even if some of the neurons are not functioning. That is, they are very robust to error or failure.
My main interest at the moment is neural networks but what are neural networks. Well here is my understanding of the basics. What is a neural network? A Neural Network is a simulation of the structure of the brain as we currently understand it. It is a series of interconnected Neurons that allow an output pattern to be produced from an input pattern. There main advantage is that they can learn and generalise through the use of supervised training. They are often used for image categorisation due to their ability to generalise. What is a neuron? A neuron consists of a series of inputs ...
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S&P500 forecast for June 8-12, 2009 Charts represent S&P500 forecast for June 8-12, 2009. The calculations* have been performed using neural network tool and pattern similarity prediction (price and volume). *) used tools - Investment Analyzer InvAn-4 and Neural Network Stock Trend Predictor NNSTP-2 . Nothing in this piece or on this web site should be construed as investment advice in any way. Always do your own research or/and consult a qualified investment advisor. It is wise to analyze data from multiple sources and draw your own conclusions based on the soundest principles. Be aware of the risks involved in stock investments.
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FACT: When a thought (e.g. "Neuroscience is boring") happens, neurons fire. POSSIBLE INTERPERTATIONS of this FACT: 1) Mystical/Dualist: The thought caused the neurons to fire. 2) Quasi-Reductionist: The neurons firing caused the thought. (Quasi-Reductionist is my own term meant to convey that this option is not necessarily the most consistent "reductionist" view to hold due to this option's apparent retention of a certain dualism, which is made clear below.) 3) Ephiphenomenolist: The thought and the neurons firing happened simultaneously, but independentaly, neither causing the other, they just happen to always be linked. 4) Eliminative Materialist: The "thought" does not exist per ce, the only ...
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Charts represent S&P-500 forecast for October 26-30, 2009. The calculations have been performed using pattern similarity prediction - Investment Analyzer InvAn-4 and neural network tool - Neural Network Stock Trend Predictor NNSTP-2 . The tools have predicted uptrend above 1,100.
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S&P-500 Forecast for October 19-23, 2009 Charts represent S&P-500 forecast for October 19-23, 2009. The calculations have been performed using pattern similarity prediction - Investment Analyzer InvAn-4 and neural network tool - Neural Network Stock Trend Predictor NNSTP-2 . The tools have predicted fluctuation within 1%.
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Neural network classification results live view (like a movie). Free software for playing with neural networks classification. Many network architectures, different shapes of training data sets. Learning with backpropagation algorithm.
Traditionally, the term neural network had been used to refer to a network or circuit of biological neurons. The modern usage of the term often refers to artificial neural networks, which are composed of artificial neurons or nodes.
This article will explain the actual concepts and implementation of Backward Propagation Neural Networks very easily - see project code and samples, like a simple pattern detector, a hand writing detection pad, an xml based neural network processing language etc in the source zip.
Do some Brain Tumor detection using neural networks, in a very simple and easy manner. This is the story and source code of an XML based language, to help you create, train and run your own neural networks?