Spiking Neural P Systems
Explore this paper's citation graph
- Type
- article
- Published
- 2006-01-01
- Cited by
- 722
- References
- 18
- OpenAlex
- https://openalex.org/W1995799881
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:3113484
Keywords
Computer science, Neural system, Neuroscience, Biology
References
- Handbook of formal languages, vol. 3: beyond words
- A New Class of Symbolic Abstract Neural Nets: Tissue P Systems
- Turing’s Connectionism
- Pulsed Neural Networks
- Designing DBMS support for the temporal dimension
- Computation: Finite and Infinite Machines
- Multifaceted physiological response allows yeast to adapt to the loss of the signal recognition particle-dependent protein-targeting pathway.
- Computing with Membranes
- Computing with spikes
- Incorporating the Temporal Dimension in a GIS
- Molecular Biology of the Cell (4th Ed)
- Spiking Neuron Models
- SPIKING NEURON MODELS Single Neurons , Populations , Plasticity
- On Symport/Antiport P Systems and Semilinear Sets
- The time dimension of computation models
Cited by
- On Some Classes of Sequential Spiking Neural P Systems
- Spiking Neural P Systems With Rules on Synapses Working in Maximum Spikes Consumption Strategy
- A Novel Clustering Algorithm Inspired by Membrane Computing
- Spiking Neural P Systems with Astrocyte-Like Control
- Reliable Arithmetic Circuit Design Inspired by SNP Systems
- Membrane computing, neural inspirations, gene assembly in ciliates
- The process matters: cyber security in industrial control systems
- Compositional Synthesis of Safety Controllers
- Scalable multi-core model checking
- Web Service Growing Pains: Understanding Services and Their Clients
- Resilient in-network aggregation for vehicular networks
- Test Suite Comprehension for Modular and Dynamic Systems
- Performance Optimization of Multi-Tenant Software Systems
- The (in)security of proprietary cryptography
- Applications of Evolutionary Computation to Cryptology ; Primjene evolucijskog računarstva u kriptologiji
- Performance analysis of real-time task systems using timed automata
- Novel Methods for Learning and Adaptation in Chemical Reaction Networks
- Spiking neural P systems with homogeneous neurons and synapses
- Software analysis methods for resource-sensitive systems
- On string languages generated by sequential spiking neural P systems based on the number of spikes
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