In this paper, on-line training of neural networks is investigated in the context of computer-assisted colonoscopic diagnosis. A memory-based adaptation of the learning rate for t...
George D. Magoulas, Vassilis P. Plagianakos, Micha...
The paper examines characteristics of interactive learning between human tutors and a robot having a dynamic neural network model which is inspired by human parietal cortex functio...
Jun Tani, Ryunosuke Nishimoto, Jun Namikawa, Masat...
Abstract--This paper is concerned with the robust synchronization problem for an array of coupled stochastic discrete-time neural networks with time-varying delay. The individual n...
Abstract-- A major drawback of artificial neural networks (ANNs) is their black-box character. This is especially true for recurrent neural networks (RNNs) because of their intrica...
A multilayer neural network based on multivalued neurons (MLMVN) is a neural network with a traditional feedforward architecture. At the same time, this network has a number of spe...
Igor N. Aizenberg, Dmitriy Paliy, Jacek M. Zurada,...
In this paper, several sufficient conditions are established for the global asymptotic stability of recurrent neural networks with multiple time-varying delays. The Lyapunov
The objective of this research is to construct parallel models that simulate the behavior of artificial neural networks. The type of network that is simulated in this project is t...
A novel framework for audio-assisted dialogue detection based on indicator functions and neural networks is investigated. An indicator function defines that an actor is present a...
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Abstract. The protein family classification problem, which consists of determining the family memberships of given unknown protein sequences, is very important for a biologist for ...