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About jkflying

  • Rank
    LAVA groupie
  • Birthday 10/07/1989

Profile Information

  • Gender
  • Location
    Cape Town, South Africa

LabVIEW Information

  • Version
    LabVIEW 2011
  • Since
  1. asbo, ShaunR: How would you suggest I place clusters within clusters within clusters within... (dynamically)? I'm desperate for speed, and if it means sacrificing OOP design I'm willing to try it, but as far as I can tell LV specifies cluster contents pretty rigidly. Doing a prev/next doesn't work in a kd tree because we have a large number of dimensions... and implicit kd trees will give this type of structure but use huge amounts of memory (curse of dimensionality and all that). As you'll see in my project, I've already tried a simple brute force method with a simple array subtract/square/s
  2. I am writing a performance-sensitive application which requires the use of a nearest-neighbor lookup. Originally I used a brute-force method, but unfortunately this gets to be very slow as the data size increases . I have a point cloud of ~100k points in 2D, and need around 50k nearest neighbor lookups per second as a minimum performance requirement. As a solution I wrote a kd-tree in .Net and used LabView to call the .Net dll. However, I discovered that each .Net transaction carries with it about a 0.5ms delay. I've tried bunching the data up into groups, but this only helps so much, as I am
  3. What will happen for multi-dimensional arrays? Will only one terminal be required?
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