- PII
- S30345480S0544126925040058-1
- DOI
- 10.7868/S3034548025040058
- Publication type
- Article
- Status
- Published
- Authors
- Volume/ Edition
- Volume 54 / Issue number 4
- Pages
- 310-322
- Abstract
- A model, methodology and software tools for simulating a spiking neural network in the training mode considering the features of the operation of memristive crossbar arrays were developed. The impact of voltage drops on interconnects, the discrete step of adjusting the conductivity levels of memristive elements and the nonlinearity of their volt-ampere characteristics on the effectiveness of implementing spiking neural network training algorithms was studied. Results of testing the spiking neural network in the training mode and inference mode in the task of image recognition using the developed simulation method, taking into account the characteristics of experimentally fabricated memristive structures, are presented.
- Keywords
- импульсные нейронные сети аппаратное исполнение мемристивный кроссбар-массив
- Date of publication
- 20.05.2025
- Year of publication
- 2025
- Number of purchasers
- 0
- Views
- 73
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