Optimizing stochastic gradient descent algorithms for serially addressed adaptive-optics wavefront modulators

Appl Opt. 2007 Oct 20;46(30):7566-72. doi: 10.1364/ao.46.007566.

Abstract

High-resolution adaptive-optical systems with thousands to millions of pixels will most likely have to employ serial- or matrix-addressed spatial light modulators (e.g., microelectromechanical-system-on-VLSI spatial light modulators). We compare parallel gradient descent adaptive-optics algorithms with serial gradient descent algorithms running on serially addressed modulators. While serial algorithms have previously been shown to require more iterations than parallel algorithms, we show that, because of the limitations of the databus, each serial iteration of the algorithm on a serial modulator requires significantly less time to complete than a parallel iteration, thereby favoring the serial algorithm when time to convergence is used as the performance metric. Thus, such high-resolution serially addressed devices are generally better matched to the serial-update wavefront correction algorithm owing to the data load penalty imposed by the bandwidth-limited databus of these modulators.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Electronics
  • Equipment Design
  • Image Enhancement
  • Image Processing, Computer-Assisted
  • Models, Theoretical
  • Optics and Photonics*
  • Signal Processing, Computer-Assisted
  • Stochastic Processes