Title :
A Neural Network Model Using Extended Feature-Based Neuron: NNDFF
Author :
Yang, Seokhwan ; Chung, Mokdong
Author_Institution :
Dept. of Comput. Eng., Pukyong Nat. Univ., Busan, South Korea
Abstract :
The neural network is useful algorithm to adopt for unknown context in the artificial intelligence technology as one of the core elements of the smart robot. However, it has several problems to be utilized in the real world due to the recurrent structure. This paper suggests a new neural network model using the distance between input point and each neuron, feature of neuron, and access frequency to neuron (NNDFF) based on the non-recurrent structure.
Keywords :
artificial intelligence; radial basis function networks; robots; NNDFF; artificial intelligence technology; extended feature-based neuron; input point-neuron distance; neural network model; neuron access frequency; neuron feature; recurrent structure; smart robot; Artificial neural networks; Biological neural networks; Brain modeling; Computational modeling; Data models; Neurons; Pattern recognition; NNDFF; neural network; non-recurrent structure;
Conference_Titel :
Network-Based Information Systems (NBiS), 2012 15th International Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4673-2331-4
DOI :
10.1109/NBiS.2012.26
