A deep cascade neural network based on extended neo-fuzzy neurons and its adaptive learning algorithm
Zhengbing Hu, Yevgeniy V. Bodyanskiy, Oleksii K. Tyshchenko · 2017 IEEE First Ukraine Conference on Electrical and Computer Engineering (UKRCON) · 2017
An architecture and learning methods for deep neural networks that increase a number of layers and adjust their synaptic weights in an online mode are proposed in the article. The system's architecture is based on nodes of a special type (extended neo-fuzzy neurons) which possess enhanced approximating properties. A main feature of the proposed network is a learning process for each node that is performed sequentially in an online mode.