Application of Chaotic Automata to Improve the Pattern Recognition Ability of Attractor Neural Networks

Título:

Application of Chaotic Automata to Improve the Pattern Recognition Ability of Attractor Neural Networks

Autor:

Marcio Argollo Ferreira de Menezes

Ano:

1998

DOI:

10.1142/S0129183198000364

Revista:

International Journal of Modern Physics C

ISSN:

01291831

Tags:

Física Computacional

optimização combinatorial

Idioma:

Inglês

Buscar essa publicação no Google Acadêmico

Publicações com a mesma autoria

Directed rigidity and bootstrap percolation in 1+1 dimensions

Separating Internal and External Dynamics of Complex Systems

Impact of Limited Solvent Capacity on Metabolic Rate, Enzyme Activities, and Metabolite Concentrations of S. cerevisiae Glycolysis

First-order transition in small-world networks

Evolving cellular automata for diversity generation and pattern recognition: deterministic versus random strategy

Why trees live longer?

Hot spots and universality in network dynamics

Emergence of clusters in growing networks with ageing

Geometric phase-transition on systems with sparse long-range connections

Detecting and modelling delayed density-dependence in abundance time series of a small mammal (Didelphis aurita)