A forecast-based STDP rule suitable for neuromorphic implementation Selected Papers from IJCNN 2011

• Published in: Neural networks Vol. 32; pp. 3 - 14
• Main Authors: DAVIES, S, GALLUPPI, F, RAST, A. D, FURBER, S. B
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier 2012
• Subjects: Applied sciences; Artificial intelligence; Biological and medical sciences; Central nervous system; Central neurotransmission. Neuromudulation. Pathways and receptors; Computer science; control theory; systems; Connectionism. Neural networks; Electronics; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; Integrated circuits; Integrated circuits by function (including memories and processors); Peripheral nervous system. Autonomic nervous system. Neuromuscular transmission. Ganglionic transmission. Electric organ; Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices; Vertebrates: nervous system and sense organs; Hardware complexity; STDP; Storage access; Biomimetics; Efficiency; Bandwidth; Synaptic plasticity; Izhikevich; SpiNNaker; Membrane potential; Spiking; Statistical analysis; Event management; Neural network; Real time; Computational complexity; Long term; Unsupervised learning; Time To Spike; Spike potential; Reactive system; Synapse; Response time; Neuromorphic; Forecast; Reliability; Excitatory postsynaptic potential; Simulator
• ISSN: 0893-6080; 1879-2782