: The contribution concerns the design of a generalised functional-link neural network with internal dynamics and its applicability to system identification by means of multi-input...
This paper studies the use of discrete-time recurrent neural networks for predicting the next symbol in a sequence. The focus is on online prediction, a task much harder than the c...
We investigate the behaviour of a neural network model consisting of three neurons with delayed self and nearest-neighbour connections. We give analytical results on the existence...
This paper presents a neuromorphic model of two olfactory signalprocessing primitives: chemotopic convergence of olfactory receptor neurons, and center on-off surround lateral inh...
— Inspired by the universal laws governing different kinds of complex networks, we propose a scale-free highlyclustered echo state network (SHESN). Different from echo state netw...