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jamesjun edited this page Dec 6, 2017 · 4 revisions
  • Calculate Rho (density) for spiking event whose peak site occurs at site K (n1 events)
  • Rho = (# neighbors with distance < dc) / # neighbors.
  • Neighboring events include those whose peak is at site K (n1 events), or whose second highest peak is at site K (n2 spikes). Thus, there are n1+n2 neighboring events for n1 events at site K.
  • To deal with probe drift, events that occur close in time are considered as neighbors. Otherwise, temporally proximal neighbors are considered such that |to_i-to_j| < (n1+n2)/P.nTime_clu; to_i: temporal order of spike i; to_j: temporal order of spike j (Graphics to be added)

Syntax

  • vrRho1 = cuda_rho_(mrFet12, viiSpk12_ord, n1, n2, dc2, P)

Input

  • mrFet12: Feature matrix (nFeatures x (n1+n2): single)
  • viiSpk12_ord: Temporal order of spikes for a given set of spikes ((n1+n2) x 1: int32); 1 <= viiSpk12_ord <= (n1+n2).
  • n1: number of spikes whose peak site (S0.viSite_spk) occurs at a given site
  • n2: number of spikes whose next highest peak site (S0.viSite2_spk) occurs at a given site
  • dc2: distance-cutoff squared
  • P: Parameters struct (P)

Output

  • vrRho1: Local density for each spike (n1 x 1: single)

Operations

  • Initialize the CUDA kernel object
  • Allocate GPU memory
  • Run the CUDA code to compute rho (jrc3_cuda_rho.cu)
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