System identification based on point processes and correlation densities. II. The refractory neuron model

DOI10.1016/0025-5564(88)90023-5zbMath0658.92006OpenAlexW4248884537MaRDI QIDQ1111957

Henk F. P. van den Boogaard

Publication date: 1988

Published in: Mathematical Biosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0025-5564(88)90023-5

zbMATH Keywords

feedbackapproximationssimulationsneuronal modellinear filtercharacteristic functionalsnonlinear relationsaction potentialsneuronal firingauto-correlation densitiescross-correlation densitiesexponential recoveryoutput point processself-exciting output process

Mathematics Subject Classification ID

Physiological, cellular and medical topics (92Cxx)

Related Items (1)

System identification based on point processes and correlation densities. I: The nonrefractory neuron model

Cites Work

• Maximum likelihood estimation of Hawkes' self-exciting point processes
• Stochastic formulation of neural interaction
• A new statistical method for identifying interconnections between neuronal network elements
• Maximum likelihood estimations in a nonlinear self-exciting point process model
• The identification of point process systems
• System identification based on point processes and correlation densities. I: The nonrefractory neuron model
• On the theory of optimal control. Sufficient coordinates
• The modeling of randomly modulated jump processes
• Spectra of some self-exciting and mutually exciting point processes
• Further results for Gauss-Poisson processes
• The probability generating functional
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