Stability study of hybrid MOS memristor memory using modified particle swarm optimization method
The problem of stability assessment of nanoelectronic structures including hybrid transistor-memristor non-volatile memory is considered. The results of the study of processes in nanoelectronic structures using memristors indicate that in addition to the usual parameter drift inherent in semiconductor devices, new unique effects arise in them, in particular, such effects that lead to uncertainty in the evaluation of the state of memristor memory cells. The study of such effects is in its infancy, in part due to the lack of models that allow full investigation of parameter variability and state drift of memristors. In this regard, we propose to use the metaheuristic particle swarm method which allows us to evaluate the stability of hybrid transistor-memristor memory. The methods of topological and parametric analysis of nanoelectronic structures with memristors, the method of interval analysis of similar structures, the method of particle swarm optimization for solving interval algebraic and differential equations are used in this work. A structuralparametric model of a hybrid memristor-based memory device is proposed, taking into account finite increments of their parameters caused by the influence of external and internal factors. An algorithm for estimating the parameters of a hybrid memristor-based memory device using a modified particle swarm optimization method is developed. Interval mathematical models serve as a basis for the development of new principles of organization of ultra-dense nonvolatile memory and create prerequisites for new approaches to the organization of computations in memory. The computational algorithm based on the method of particle swarm optimization allows us to evaluate the performance of hybrid metaloxide-semiconductor structures (MOS structures) with memristors under real operating conditions, resulting in the possibility to expand the scope of application of devices using quantum effects in various technical application
Authors
- А В Бондарев (ORCID: https://orcid.org/0000-0002-2933-9599)
- В. Н. Ефанов
Publication Details
- Journal
- Scientific and technical journal of information technologies mechanics and optics
- Published
- 2024-12-01
- DOI
- https://doi.org/10.17586/2226-1494-2024-24-6-1059-1065
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00