Pages that link to "Item:Q2565995"

The following pages link to General methodology for nonlinear modeling of neural systems with Poisson point-process inputs (Q2565995):

Displaying 8 items.

• Identifying odd/even-order binary kernel slices for a nonlinear system using inverse repeat m-sequences (Q308810) (← links)
• The quantitative single-neuron modeling competition (Q999399) (← links)
• Identification of MGB cells by Volterra kernels. III. A glance into the black box (Q1087494) (← links)
• Decomposition of neural systems with nonlinear feedback using stimulus-response data (Q1585173) (← links)
• A common goodness-of-fit framework for neural population models using marked point process time-rescaling (Q1628363) (← links)
• A nonlinear autoregressive Volterra model of the Hodgkin-Huxley equations (Q1746820) (← links)
• System identification based on point processes and correlation densities. I: The nonrefractory neuron model (Q1820087) (← links)
• A Metric Space for Point Process Excitations (Q5076362) (← links)