A data-driven regularization approach for template matching in spike sorting with high-density neural probes.
Jasper WoutersFabian KloostermanAlexander BertrandPublished in: EMBC (2019)
Keyphrases
- template matching
- high density
- data driven
- spike trains
- spiking neurons
- low density
- matching algorithm
- close proximity
- neuronal networks
- cross correlation
- data center
- object recognition
- high power
- image matching
- hodgkin huxley
- thin film
- deformable templates
- target recognition
- magnetic recording
- high bandwidth
- bio inspired
- magnetic tape
- spiking neural networks
- neural fuzzy
- hit or miss transform
- feature extraction
- action potentials
- chamfer matching
- low cost
- biologically plausible