Publications

2024

SENSORS, 24 (3). ISSN 1424-8220

Hologram Noise Model for Data Augmentation and Deep Learning

Authors

Terbe, Dániel

Orzó, László

Bicsák, Barbara

Zarándy, Ákos

2002

In: Cellular Neural Networks and Their Applications. Proceedings of the 7th IEEE International Workshop.

Application of analogic CNN algorithms in telemedical neuroradiology

Authors

Szabó, T.

Barsi, P.

Szolgay, Péter

Editors

Tetzlaff, R

2002

INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, 30 (2-3)., pp. 139-245.

A behavioural modelling technique for visual microprocessor mixed-signal VLSI chips

Authors

Földesy, Péter

Rodríguez-Vázquez, Á.

2002

INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, 30 (2-3)., pp. 247-270.

Optimal path finding with space- and time-variant metric weights via multi-layer CNN

Authors

Kim, H.

Son, H.

Roska, Tamás

Chua, LO

2002

In: Cellular Neural Networks and Their Applications. Proceedings of the 7th IEEE International Workshop.

Improvement of the method for uncoupled binary input-output CNN template decomposition

Authors

Kék, László

Editors

Tetzlaff, R

2002

INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, 30 (2-3)., pp. 287-312.

Adaptive image sensing and enhancement using the cellular neural network universal machine

Authors

Brendel, M.

Roska, Tamás

2002

In: Proceedings of the 41st IEEE conference on decision and control. Las Vegas.

New methods for the statistical analysis of Hidden Markov models

Authors

Gerencsér, László

Molnár-Sáska, Gábor

Michaletzky, György

Tusnády, G.

Vágó, ZS

2002

INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, 30 (2-3)., pp. 181-193.

On the rectangular grid representation of general CNN networks

Authors

Radványi, András

2002

In: Cellular Neural Networks and Their Applications. Proceedings of the 7th IEEE International Workshop.

Supervised and unsupervised art-like classifications of binary vectors on the CNN universal machine

Authors

Bálya, Dávid

Roska, Tamás

Editors

Tetzlaff, R

2002

INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS, 12 (10)., pp. 2051-2068.

CNN dynamics represents a broader class than PDEs

Authors

Gilli, M.

Roska, Tamás

Chua, LO

Civalleri, PP

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Publications

Hologram Noise Model for Data Augmentation and Deep Learning

Application of analogic CNN algorithms in telemedical neuroradiology

A behavioural modelling technique for visual microprocessor mixed-signal VLSI chips

Optimal path finding with space- and time-variant metric weights via multi-layer CNN

Improvement of the method for uncoupled binary input-output CNN template decomposition

Adaptive image sensing and enhancement using the cellular neural network universal machine

New methods for the statistical analysis of Hidden Markov models

On the rectangular grid representation of general CNN networks

Supervised and unsupervised art-like classifications of binary vectors on the CNN universal machine

CNN dynamics represents a broader class than PDEs