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Synaptic Learning With Augmented Spikes

IEEE transaction on neural networks and learning systems, 2022-03, Vol.33 (3), p.1134-1146

2022

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Numerical Spiking Neural P Systems

IEEE transaction on neural networks and learning systems, 2021-06, Vol.32 (6), p.2443-2457

2021

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Local Synchronization on Asynchronous Tissue P Systems With Symport/Antiport Rules

IEEE transactions on nanobioscience, 2020-04, Vol.19 (2), p.315-320

2020

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Spiking Neural P Systems With Learning Functions

IEEE transactions on nanobioscience, 2019-04, Vol.18 (2), p.176-190

2019

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Cell-Like Spiking Neural P Systems With Request Rules

IEEE transactions on nanobioscience, 2017-09, Vol.16 (6), p.513-522

2017

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Tissue P Systems With Channel States Working in the Flat Maximally Parallel Way

IEEE transactions on nanobioscience, 2016-10, Vol.15 (7), p.645-656

2016

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Cell-Like P Systems With Channel States and Symport/Antiport Rules

IEEE transactions on nanobioscience, 2016-09, Vol.15 (6), p.555-566

2016

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On Languages Generated by Cell-Like Spiking Neural P Systems

IEEE transactions on nanobioscience, 2016-07, Vol.15 (5), p.455-467

2016

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On the Universality and Non-Universality of Spiking Neural P Systems With Rules on Synapses

IEEE transactions on nanobioscience, 2015-12, Vol.14 (8), p.960-966

2015

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Identifying Driver Nodes in the Human Signaling Network Using Structural Controllability Analysis

IEEE/ACM transactions on computational biology and bioinformatics, 2015-03, Vol.12 (2), p.467-472

2015

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Spiking Neural P Systems With Rules on Synapses Working in Maximum Spikes Consumption Strategy

IEEE transactions on nanobioscience, 2015-01, Vol.14 (1), p.38-44

2015

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Normal Forms for Some Classes of Sequential Spiking Neural P Systems

IEEE transactions on nanobioscience, 2013-09, Vol.12 (3), p.255-264

2013

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Normal Forms of Spiking Neural P Systems With Anti-Spikes

IEEE transactions on nanobioscience, 2012-12, Vol.11 (4), p.352-359

2012

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Performing Four Basic Arithmetic Operations With Spiking Neural P Systems

IEEE transactions on nanobioscience, 2012-12, Vol.11 (4), p.366-374

2012

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An Unenumerative DNA Computing Model for Vertex Coloring Problem

IEEE transactions on nanobioscience, 2011-06, Vol.10 (2), p.94-98

2011

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Small Universal Spiking Neural P Systems Working in Exhaustive Mode

IEEE transactions on nanobioscience, 2011-06, Vol.10 (2), p.99-105

2011

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Synaptic Learning With Augmented Spikes

Numerical Spiking Neural P Systems

Local Synchronization on Asynchronous Tissue P Systems With Symport/Antiport Rules

Spiking Neural P Systems With Learning Functions

Cell-Like Spiking Neural P Systems With Request Rules

Tissue P Systems With Channel States Working in the Flat Maximally Parallel Way

Cell-Like P Systems With Channel States and Symport/Antiport Rules

On Languages Generated by Cell-Like Spiking Neural P Systems

On the Universality and Non-Universality of Spiking Neural P Systems With Rules on Synapses

Identifying Driver Nodes in the Human Signaling Network Using Structural Controllability Analysis

Spiking Neural P Systems With Rules on Synapses Working in Maximum Spikes Consumption Strategy

Normal Forms for Some Classes of Sequential Spiking Neural P Systems

Normal Forms of Spiking Neural P Systems With Anti-Spikes

Performing Four Basic Arithmetic Operations With Spiking Neural P Systems

An Unenumerative DNA Computing Model for Vertex Coloring Problem

Small Universal Spiking Neural P Systems Working in Exhaustive Mode

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