In this paper we describe a complete design methodology for a globally asynchronous onchip communication network connecting both locally-synchronous and asynchronous modules. Sync...
Jens Muttersbach, Thomas Villiger, Wolfgang Fichtn...
An enhanced self-organizing incremental neural network (ESOINN) is proposed to accomplish online unsupervised learning tasks. It improves the self-organizing incremental neural ne...
Background: The exploration of the structural topology and the organizing principles of genomebased large-scale metabolic networks is essential for studying possible relations bet...
Jing Zhao, Hong Yu, Jianhua Luo, Zhi-Wei Cao, Yi-X...
This paper presents FC networks that are instantaneously trained neural networks that allow rapid learning of non-binary data. These networks, which generalize the earlier CC netw...
An original methodology, called backward model tracing to model student performance which features a profitable integration of the bug collection and bug construction techniques i...