Title :
An optimal multilayer neural interpolating (OMNI) net in a generalized Fock space setting
Author :
deFigueredo, R.J.P.
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., Irvine, CA
Abstract :
As a generalization and extension of the OI (optimal interpolative) artificial neural network, an OMNI (optimal multilayer neural interpolative) net is proposed. An OMNI net is an interconnected system of OI nets in either feedforward, feedback, or recurrent configuration. The synaptic weights for the OMNI net can be calculated by closed-form expressions. For the feedforward configuration a forward-propagation algorithm is described. OMNI nets can be used for classification and interpretation of complex patterns. As an example, an OMNI net model for the six-layer cortical column of the human brain is described
Keywords :
feedforward neural nets; interpolation; recurrent neural nets; OMNI net; OMNI net model; artificial neural network; closed-form expressions; feedforward configuration; forward-propagation algorithm; generalized Fock space setting; human brain; optimal interpolative net; optimal multilayer neural interpolative net; pattern classification; pattern interpretation; six-layer cortical column; synaptic weights; Artificial neural networks; Brain modeling; Clustering algorithms; Computer networks; Humans; Interpolation; Mathematics; Neurofeedback; Nonhomogeneous media; Signal processing algorithms;
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
DOI :
10.1109/IJCNN.1992.287221
