This journal covers a wide range of issues in information optics, such as optical memory, mechanisms for optical data recording and processing, photosensitive materials, optical and optoelectronic components, and many other related topics. It reports on theoretical researches and applications in different fields, including: data recording, processing and storage with the use of optical and holographic methods; associative memory (including biological memory), mathematical models and implementations of neuron systems for data processing and management; optoelectronic matrix devices and multiple-unit nanostructures for new data processing and storage systems. The journal pays particular attention to research in the field of neural net systems that may, by Endowing computation means with intelligence, lead to a new generation of computing devices.PEER REVIEW Optical Memory and Neural Networks is a peer reviewed journal. We use a single blind peer review format. Our team of reviewers includes 38 experts from 17 countries. The average period from submission to first decision in 2018 was 30 days, and that from first decision to acceptance was 30 days. The rejection rate for submitted manuscripts in 2018 was 35%. The final decision on the acceptance of an article for publication is made by the Editors-in-Chief. Any invited reviewer who feels unqualified or unable to review the manuscript due to the conflict of interests should promptly notify the editors and decline the invitation. Reviewers should formulate their statements clearly in a sound and reasoned way so that authors can use reviewer’s arguments to improve the manuscript. Personal criticism of the authors must be avoided. Reviewers should indicate in a review (i) any relevant published work that has not been cited by the authors, (ii) anything that has been reported in previous publications and not given appropriate reference or citation, (ii) any substantial similarity or overlap with any other manuscript (published or unpublished) of which they have personal knowledge.
Optical Memory and Neural Networks
Description
Identifiers
ISSN | 1060-992X |
e-ISSN | 1934-7898 |
Publisher
Pleiades Publishing
Additional information
Data set: Springer
Articles
Optical Memory and Neural Networks > 2019 > 28 > 3 > 192-203
We discuss the problem of mathematical and computer modeling of nonlinear controllable dynamical systems with incomplete knowledge about the object of modeling and the conditions of its operation. The suggested approach is based on a merging of theoretical knowledge for the system with training tools of artificial neural network (ANN) field. We present an extension of previously proposed semi-empirical...
Optical Memory and Neural Networks > 2019 > 28 > 3 > 165-174
In the present paper we analyzed a change in the density of states of a two-dimensional Ising model when a next-next-neighbor interaction is introduced. In other words, we examined two-dimensional lattices with diagonal connections. The same as in a three-dimensional model in this case each spin has 6 connections. Since the model is planar, we can calculate the free energy and other characteristics...
Optical Memory and Neural Networks > 2019 > 28 > 3 > 185-191
An overview of known works in active vision area and our recent results on application of the foveal visual preprocessor to detect the head motion parameters are presented. In overview, the main directions of research and development in the field of artificial foveal active vision have been considered. It is justified that: (i) for a successful solution of complex problems in this area and creation...