The cellular learning automaton (CLA), which is a4 combination of cellular automaton (CA) and learning automaton5 (LA), is introduced recently. This model is superior to CA because...
In this paper, an invariant set of the weight of the perceptron trained by the perceptron training algorithm is defined and characterized. The dynamic range of the steady state va...
Charlotte Yuk-Fan Ho, Bingo Wing-Kuen Ling, Herber...
A generalized or tunable-kernel model is proposed for probability density function estimation based on an orthogonal forward regression procedure. Each stage of the density estimat...
Abstract--This paper is concerned with the networked synchronization control problem of coupled dynamic networks (CDNs) with time-varying delay. First, both the data packet dropout...
We propose a new dynamic model which can be used within blob trackers to track the target's center of gravity. A strong point of the model is that it is designed to track a va...
Matej Kristan, Stanislav Kovacic, Ales Leonardis, ...
We describe a cognitive architecture for creating more robust intelligent systems by executing hybrids of algorithms based on different computational formalisms. The architecture ...
Nicholas L. Cassimatis, Perrin G. Bignoli, Magdale...
In this paper, we propose two novel techniques, which successfully address several major problems in the field of particle swarm optimization (PSO) and promise a significant breakt...
Serkan Kiranyaz, Turker Ince, E. Alper Yildirim, M...
In this paper we propose a credal representation of the interval probability associated with a belief function (b.f.), and show how it relates to several classical Bayesian transfo...