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...
[more]
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.
We've all got a very sophisticated processing unit – the brain – that can perform some remarkable tasks.
Despite their speed and memory capacity, silicon-based computers struggle to emulate it. The branch of computer science called Artificial Intelligence tries to narrow the gap, and one of the basic tools of AI is the neural network. So let's take a look at what the neural network can do.
Over the years, Artificial Intelligence has had its...
The geochemical discriminate diagrams help to distinguish the volcanics recovered from different tectonic settings but these diagrams tend to group the ocean floor basalts (OFB) under one class i.e., as mid-oceanic ridge basalts (MORB). Hence, a method is specifically needed to identify the OFB as normal (N-MORB), enriched (E-MORB) and ocean island basalts (OIB).We have applied Artificial Neural Network (ANN) technique as a supervised Learning...
We've all got a very sophisticated processing unit – the brain – that can perform some remarkable tasks. Despite their speed and memory capacity, silicon-based computers struggle to emulate it. The branch of computer science called Artificial Intelligence tries to narrow the gap, and one of the basic tools of AI is the neural network. So let's take a look at what the neural network can do. Over the years, Artificial Intelligence has had its...
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?
Researchers at Howard Hughes Medical Institute have developed a method to dupe nerve cells to manufacture a protein that lights up when those cells depolarize. The fluorescent indicator, GCaMP3, for the first time allows live monitoring of large number of neurons as they undergo single action potentials. This amazing functional modality might open new possibilities in the study of neural networks. Looking at the structure of GCaMP2, Looger...
Background:
Our aim is to investigate the ability of neural networks to model different two-locus disease models. We conduct a simulation study to compare neural networks with two standard methods, namely logistic regression models and multifactor dimensionality reduction. One hundred data sets are generated for each of six two-locus disease models, which are considered in a low and in a high risk scenario. Two models represent independence...
I keep receiving the same output for each record when I run it on the test data. I've tried numerous things...any suggestions? I've worked on this for almost twelve hours straight, not counting previous work. I'm hoping one of you guys/gals who know whats going on can point me in the right...
"Future projection of the energy dependency of Turkey using artificial neural networkSözen, AdnanEnergy dependency (ED) implies the extent to which an economy relies upon imports in order to meet its energy needs. The ED is calculated as net imports divided by the sum of gross inland energy consumption plus bunkers. This study aims at obtaining numerical equations to estimate of Turkey's energy dependency based on basic energy indicators and...
Background:
Recently, extensive studies have been carried out on arrhythmia classification algorithms using artificial intelligence pattern recognition methods such as neural network. To improve practicality, many studies have focused on learning speed and the accuracy of neural networks. However, algorithms based on neural networks still have some problems concerning practical application, such as slow learning speeds and unstable performance...