A reproducing kernel Hilbert space framework for spike train signal processing.
about
A tensor-product-kernel framework for multiscale neural activity decoding and controlStatistical analysis and decoding of neural activity in the rodent geniculate ganglion using a metric-based inference system.Restoring Behavior via Inverse Neurocontroller in a Lesioned Cortical Spiking Model Driving a Virtual Arm.A simple algorithm for averaging spike trains.Reconstruction of Sensory Stimuli Encoded with Integrate-and-Fire Neurons with Random Thresholds.Strictly positive-definite spike train kernels for point-process divergences.An information-geometric framework for statistical inferences in the neural spike train space.Estimating summary statistics in the spike-train space.Improved similarity measures for small sets of spike trains.Neural decoding with kernel-based metric learning.Biologically-Inspired Spike-Based Automatic Speech Recognition of Isolated Digits Over a Reproducing Kernel Hilbert Space.Nonlinear decoding of a complex movie from the mammalian retina.
P2860
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P2860
A reproducing kernel Hilbert space framework for spike train signal processing.
description
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name
A reproducing kernel Hilbert space framework for spike train signal processing.
@en
A reproducing kernel Hilbert space framework for spike train signal processing.
@nl
type
label
A reproducing kernel Hilbert space framework for spike train signal processing.
@en
A reproducing kernel Hilbert space framework for spike train signal processing.
@nl
prefLabel
A reproducing kernel Hilbert space framework for spike train signal processing.
@en
A reproducing kernel Hilbert space framework for spike train signal processing.
@nl
P2860
P1433
P1476
A reproducing kernel Hilbert space framework for spike train signal processing
@en
P2093
António R C Paiva
José C Príncipe
P2860
P304
P356
10.1162/NECO.2008.09-07-614
P50
P577
2009-02-01T00:00:00Z