Point process analysis of noise in early invertebrate vision
Fig 4
The integrate-fire-Snyder outperforms other machine learning and photon estimating schemes across intensity.
The integrate-fire was tested against Gaussian processes and optimised finite impulse response filters which used the bump data directly. It was also compared to other schemes that also estimated photons for processing with Snyder filters. These fired photons based on pure current thresholds or bump gradients. Data is shown for the interrupted model at γ = 20 for a given representative light model trajectory of 7000-8000 photons. The integrate-fire showed superior overall performance. Consistent results have also been obtained for γ = 5. This motivated the use of the integrate-fire-Snyder as a cascade estimator.