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» Introduction to artificial neural networks
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IEEEICCI
2002
IEEE
14 years 27 days ago
Quasi-Morphism and Comprehensibility of Rules in Inductive Learning
We present a model of creating a hierarchical set of rules that encode generalizations and exceptions derived from induction learning. The rules use the input features directly an...
Wiphada Wettayaprasit, Chidchanok Lursinsap, Chee-...
AMC
2008
99views more  AMC 2008»
13 years 8 months ago
Markov chain network training and conservation law approximations: Linking microscopic and macroscopic models for evolution
In this paper, a general framework for the analysis of a connection between the training of artificial neural networks via the dynamics of Markov chains and the approximation of c...
Roderick V. N. Melnik
EVOW
2008
Springer
13 years 9 months ago
Composing Music with Neural Networks and Probabilistic Finite-State Machines
In this paper, biological (human) music composition systems based on Time Delay Neural Networks and Ward Nets and on a probabilistic Finite-State Machine will be presented. The sys...
Tomasz Michal Oliwa, Markus Wagner
IJCNN
2006
IEEE
14 years 2 months ago
TempUnit: A bio-inspired neural network model for signal processing
– We have developed and tested a novel artificial neural network for the processing of temporal signals. The working of the units (TempUnit) is based on the mechanism of temporal...
Olivier F. Manette, Marc A. Maier
AGI
2011
12 years 11 months ago
Systematically Grounding Language through Vision in a Deep, Recurrent Neural Network
Human intelligence consists largely of the ability to recognize and exploit structural systematicity in the world, relating our senses simultaneously to each other and to our cogni...
Derek Monner, James A. Reggia