Abstract
The variable resistors changing their resistance during the process of functioning may become the basis for creation of neural networks elements (synapses, neurons, etc.). The processes leading to resistance change are extremely complicated and are not yet amenable to correct description. To master the possibilities of using the variable resistors it is reasonable to use the metaphorical modeling, i.e. to replace a complex physical system with a simple mathematical system with a small number of parameters, reproducing the important features of real system’s behavior. A simple (elementary) resistor element with state determined by a single scalar variable is considered as the modeling unit. The equations describing the change of the state variable are written down. The choices of functions and parameters in equations, as well as the methods of such elements combination with traditional electronic components (fixed resistors, capacitors, diodes, etc.) are discussed. The selection of these functions from a small set and the adjustment of several parameters allow us to obtain the characteristics close to real ones. The scheme of measuring the “volt-ampere characteristics” is considered. An example of specific selection of functions determining the resistor element behavior is given.
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The work financially supported by State Program of SRISA RAS No. 0065-2019-0003 (AAA-A19-119011590090-2).
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Kotov, V.B., Palagushkin, A.N., Yudkin, F.A. (2020). Metaphorical Modeling of Resistor Elements. In: Kryzhanovsky, B., Dunin-Barkowski, W., Redko, V., Tiumentsev, Y. (eds) Advances in Neural Computation, Machine Learning, and Cognitive Research III. NEUROINFORMATICS 2019. Studies in Computational Intelligence, vol 856. Springer, Cham. https://doi.org/10.1007/978-3-030-30425-6_38
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DOI: https://doi.org/10.1007/978-3-030-30425-6_38
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