INVESTIGADORES
JULIAN Pedro Marcelo
artículos
Título:
RTD-Based Cellular Neural Networks with Multiple Steady States
Autor/es:
M. ITOH, P. JULIÁN, L. O. CHUA
Revista:
INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS
Editorial:
World Scientific Publishing
Referencias:
Año: 2001 vol. 11 p. 2913 - 2959
ISSN:
0218-1274
Resumen:
In this paper, we study the relationship between the standard cellular neural network (CNN)
and the resonant tunneling diode (RTD)-based CNN. We investigate the functional and advanced
capabilities of a new generation of CNNs that exploit the multiplicity of steady states.
We also include in the analysis higher order CNNs. Furthermore, some methods for designing
RTD-based CNNs with multiple steady states are presented.
