Approach to analytically minimize the LCD moiré by image-based particle swarm optimization

Abstract

In this paper, we proposed a methodology to optimize the parametric window of a liquid crystal display (LCD) system, whose visual performance was deteriorated by the pixel moiré arising in between multiple periodic structures. Conventional analysis and minimization of moiré patterns are limited by few parameters. With the proposed image-based particle swarm optimization (PSO), we enable a multivariable optimization at the same time. A series of experiments was conducted to validate the methodology. Due to its versatility, the proposed technique will certainly have a promising impact on the fast optimization in LCD design with more complex configuration.

Forecasting outpatient visits using empirical mode decomposition coupled with back-propagation artificial neural networks optimized by particle swarm optimization

“…PSO is a type of swarm intelligence optimization algorithm for global optimization and has proven to be a competitor to GA when it comes to optimization problems[ 24 ].Compared with other biological evolution algorithms, PSO occupies the bigger optimization ability using simple relations [ 25 ]. It is widely used in optimization because of its need for less parameter sets and its faster convergence rate and easy escape from the local optimum compared with other algorithms[ 26 – 31 ]. At the same time, it can perform strong parallel search and global optimization.…”