Title :
Improving the efficiency of MLP back propogation learning at the classification of quasi-stationary signals
Author :
Arsiriy, E.A. ; Antoshchuk, S.G. ; Arsiri, V.A. ; Groysman, T.V.
Abstract :
Investigated efficiency improvement for the back propagation learning in batch mode of MLP at the classification of quasi-stationary signals relied on tuning the learning rate based on gradient descent algorithm and the slope angle of the neurons activation function.
Keywords :
backpropagation; gradient methods; multilayer perceptrons; neural nets; signal classification; transfer functions; MLP backpropogation learning; batch mode; gradient descent algorithm; investigated efficiency improvement; learning rate; neurons activation function; quasi-stationary signal classification; Algorithm design and analysis; Classification algorithms; Decision support systems; Hydrodynamics; Neurons; Training; Tuning; back-propagation learning; hydrodynamic flows; multilayer perceptron; quasi-stationary signals;
Conference_Titel :
Intelligent Data Acquisition and Advanced Computing Systems (IDAACS), 2011 IEEE 6th International Conference on
Conference_Location :
Prague
Print_ISBN :
978-1-4577-1426-9
DOI :
10.1109/IDAACS.2011.6072775
