Mathematics Of Artificial Neural Networks
   HOME



picture info

Mathematics Of Artificial Neural Networks
An artificial neural network (ANN) combines biological principles with advanced statistics to solve problems in domains such as pattern recognition and game-play. ANNs adopt the basic model of neuron analogues connected to each other in a variety of ways. Structure Neuron A neuron with label j receiving an input p_j(t) from predecessor neurons consists of the following components: * an ''activation'' a_j(t), the neuron's state, depending on a discrete time parameter, * an optional ''threshold'' \theta_j, which stays fixed unless changed by learning, * an ''activation function'' f that computes the new activation at a given time t+1 from a_j(t), \theta_j and the net input p_j(t) giving rise to the relation :: a_j(t+1) = f(a_j(t), p_j(t), \theta_j), * and an ''output function'' f_\text computing the output from the activation :: o_j(t) = f_\text(a_j(t)). Often the output function is simply the identity function. An ''input neuron'' has no predecessor but serves as inp ...
[...More Info...]      
[...Related Items...]     OR:     [Wikipedia]   [Google]   [Baidu]  


picture info

Pattern Recognition
Pattern recognition is the task of assigning a class to an observation based on patterns extracted from data. While similar, pattern recognition (PR) is not to be confused with pattern machines (PM) which may possess PR capabilities but their primary function is to distinguish and create emergent patterns. PR has applications in statistical data analysis, signal processing, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Pattern recognition has its origins in statistics and engineering; some modern approaches to pattern recognition include the use of machine learning, due to the increased availability of big data and a new abundance of processing power. Pattern recognition systems are commonly trained from labeled "training" data. When no labeled data are available, other algorithms can be used to discover previously unknown patterns. KDD and data mining have a larger focus on unsupervised methods and str ...
[...More Info...]      
[...Related Items...]     OR:     [Wikipedia]   [Google]   [Baidu]  



MORE