• Cover Page
• Editorial Board and Information for Authors
• Aims and Scope
• Contents
Contents
Zhirabok A. and Shumsky A.
An approach to the analysis of observability and controllability in nonlinear
systems via linear methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 507
Balachandran K. and Kokila J.
On the controllability of fractional dynamical systems . . . . . . . . . . . . . . . . . . . . . . . . . .523
Ostalczyk P.
Equivalent descriptions of a discrete-time fractional-order linear system and its stability domains . . . . . . . . .533
Dos Santos Martins V., Rodrigues M. and Diagne M.
A multi-model approach to Saint-Venant equations:
A stability study by LMIs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 539
Filasová A. and Krokavec D.
H∞ control of discrete-time linear systems constrained in state by equality
constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 551
Hladík M.
Enclosures for the solution set of parametric interval linear systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .561
Liu W.J.
Variable structure observer design for a class of uncertain systems with a time-varying delay . . . . . . . . . . . . . . .575
Zaidi A., Ould Bouamama B. and Tagina M.
Bayesian reliability models of Weibull systems: State of the art . . . . . . . .585
Djebrani S., Benali A. and Abdessemed F.
Modelling and control of an omnidirectional mobile manipulator . . . . . . . . 601
Soltani M., Chaari A. and Ben Hmida F.
A novel fuzzy c-regression model algorithm using a new error
measure and particle swarm optimization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 617
Piegat A. and Landowski M.
Optimal estimator of hypothesis probability for datamining problemswith small
samples. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .629
Jankowski N.
Graph-based generation of ameta-learning search space. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .647
Gocławski J., Sekulska-Nalewajko J. and Kuźniak E.
Neural network segmentation of images from stained
cucurbits leaves with colour symptoms of biotic and abiotic stresses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .669
Tan Y., Dong R., Chen H. and He H.
Neural network based identification of hysteresis in human meridian
systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 685
Fabijańska A.
A survey of subpixel edge detection methods for images of heat-emitting metal specimens . . . . . . . . . . . . 695
Biedrzycki R. and Arabas J.
KIS: An automated attribute induction method for classification of DNA
sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 711
Péter T.
Modeling nonlinear road traffic networks for junction control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 723
Chmaj G., Walkowiak K., Tarnawski M. and Kucharzak M.
Heuristic algorithms for optimization of task
allocation and result distribution in peer-to-peer computing systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 733
Olwal T.O., Djouani K., Kogeda O.P. and van Wyk B.J.
Joint queue-perturbed and weakly coupled power
control for wireless backbone networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .749
Formanowicz P. and Tanaś K.
The Fan–Raspaud conjecture: A randomized algorithmic approach and
application to the pair assignment problemin cubic networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .765