Understanding of the human brain functioning currently represents a challenging problem. In
contrast to usual serial computers and complicated hierarchically organized artificial man-made
systems decentralized parallel and distributed information processing principles are inherent
to the brain. Besides adaptation and learning which play a crucial role in brain functioning
oscillatory neural activity synchronization and resonance accompany the brain work.
Neural-like oscillatory network models designed by the authors for image processing allow to
elucidate the capabilities of dynamical synchronization-based types of image processing
presumably exploited by the brain. The oscillatory network models studied by means of computer
modeling and qualitative analysis are presented and discussed in the book. Some other problems
of parallel distributed information processing are also considered such as a recall process
from network memory for large-scale recurrent associative memory neural networks performance
of oscillatory networks of associative memory dynamical oscillatory network methods of image
processing with synchronization-based performance optical parallel information processing
based on the nonlinear optical phenomenon of photon echo and modeling random electric fields
of quasi-monochromatic polarized light beams using systems of superposed stochastic
oscillators. This makes the book highly interesting to researchers dealing with various aspects
of parallel information processing.
