Title :
A new ANN model and factor analysis of its optimization parameters
Author :
Meghabghab, G. ; Kandel, A.
Author_Institution :
Dept. of Comput. Sci., Valdosta State Coll., GA, USA
Firstpage :
0.708333333333333
Abstract :
A model is presented in which the neuron plays a role in the learning phase through its adaptation of two parameters: the temperature and the level of connectivity of a given neuron. This method permits a neuron to adjust its own local temperature and the local activity of the connections. An extended back-propagation algorithm that includes both synaptical and neuronal parameters is applied to a logic type of problem, specifically, the Exclusive-OR (XOR). This results in reducing the number of cycles of the learning phase
Keywords :
Boolean functions; neural nets; optimisation; Exclusive-OR; XOR; back-propagation algorithm; learning phase; logic problem; neuron; neuronal parameters; optimization parameters; synaptical parameters; Artificial neural networks; Biological system modeling; Computer networks; Computer science; Educational institutions; Information processing; Neural networks; Neurons; Supervised learning; Temperature;
Conference_Titel :
Southeastcon '93, Proceedings., IEEE
Conference_Location :
Charlotte, NC
Print_ISBN :
0-7803-1257-0
DOI :
10.1109/SECON.1993.465761
