caa a22 4500 606160094 CHVBK 20210128100628.0 cr unu---uuuuu 210128e20151101xx s 000 0 eng 10.1007/s00521-015-1857-4 doi (NATIONALLICENCE)springer-10.1007/s00521-015-1857-4 Spiking neural P systems with structural plasticity [Elektronische Daten] [Francis Cabarle, Henry Adorna, Mario Pérez-Jiménez, Tao Song] Spiking neural P (SNP) systems are a class of parallel, distributed, and nondeterministic computing models inspired by the spiking of biological neurons. In this work, the biological feature known as structural plasticity is introduced in the framework of SNP systems. Structural plasticity refers to synapse creation and deletion, thus changing the synapse graph. The "programming” therefore of a brain-like model, the SNP system with structural plasticity (SNPSP system), is based on how neurons connect to each other. SNPSP systems are also a partial answer to an open question on SNP systems with dynamism only for synapses. For both the accepting and generative modes, we prove that SNPSP systems are universal. Modifying SNPSP systems semantics, we introduce the spike saving mode and prove that universality is maintained. In saving mode, however, a deadlock state can arise, and we prove that reaching such a state is undecidable. Lastly, we provide one technique in order to use structural plasticity to solve a hard problem: a constant time, nondeterministic, and semi-uniform solution to the NP-complete problem Subset Sum. The Natural Computing Applications Forum, 2015 Membrane computing nationallicence Spiking neural P systems nationallicence Structural plasticity nationallicence Computational universality nationallicence Deadlock nationallicence Undecidability nationallicence Subset Sum nationallicence Cabarle Francis Algorithms and Complexity Lab, Department of Computer Science, University of the Philippines Diliman, 1101, Quezon City, Philippines aut Adorna Henry Algorithms and Complexity Lab, Department of Computer Science, University of the Philippines Diliman, 1101, Quezon City, Philippines aut Pérez-Jiménez Mario Department of Computer Science and AI, University of Sevilla, Avda. Reina Mercedes s/n, 41012, Sevilla, Spain aut Song Tao Key Laboratory of Image Processing and Intelligent Control, School of Automation, Huazhong University of Science and Technology, 430074, Wuhan, Hubei, China aut Neural Computing and Applications Springer London 26/8(2015-11-01), 1905-1917 0941-0643 26:8<1905 2015 26 521 https://doi.org/10.1007/s00521-015-1857-4 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-015-1857-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Cabarle Francis Algorithms and Complexity Lab, Department of Computer Science, University of the Philippines Diliman, 1101, Quezon City, Philippines aut NATIONALLICENCE 700 1- Adorna Henry Algorithms and Complexity Lab, Department of Computer Science, University of the Philippines Diliman, 1101, Quezon City, Philippines aut NATIONALLICENCE 700 1- Pérez-Jiménez Mario Department of Computer Science and AI, University of Sevilla, Avda. Reina Mercedes s/n, 41012, Sevilla, Spain aut NATIONALLICENCE 700 1- Song Tao Key Laboratory of Image Processing and Intelligent Control, School of Automation, Huazhong University of Science and Technology, 430074, Wuhan, Hubei, China aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/8(2015-11-01), 1905-1917 0941-0643 26:8<1905 2015 26 521