title: Gray-level discrete associative memory.
abstract: A gray-level discrete associative-memory neural network based on object decomposition and composition is presented. By decomposing a gray-level pattern into bipolar/binary subpatterns, a gray-level discrete associative memory can be constructed from the composition of the subpattern channel results. Preprocessing for removing dc bias and normalizing the gray-level scale is performed on the input gray-level pattern. This eliminates the mismatching and saturation problems caused by bias level, which shifts the pattern gray levels throughout the pattern. Computer-simulation and optical-experimental results for a gray-level interpattern association model are shown to be consistent with the theoretical model.
authors.forename: F T
authors.initials: FT
authors.lastname: Yu
authors.forename: C M
authors.initials: CM
authors.lastname: Uang
authors.forename: S
authors.initials: S
authors.lastname: Yin