Analysis of Mathematical Models of Memristors for Use in Logical Nanoelectronic Memory Circuits of Artificial Intelligence Systems
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The article highlights memristors as pivotal components for future micro- and nanoelectronic devices, functioning as resistors with memory that adjust conductivity based on signal transmission. Their nonlinear voltage-current characteristics enable applications in non-volatile memory, logic circuits, and neuromorphic systems, promising enhanced energy efficiency and adaptability for self-learning machines.
Advancements in Memristor Technology for AI Memory Circuits
Recent analysis highlights the potential of memristors as critical components in developing logical nanoelectronic memory circuits for artificial intelligence systems. These devices adjust their conductivity based on their signal transmission participation, representing a significant leap in micro- and nanoelectronics.
The implications of memristor technology extend beyond mere efficiency. They pave the way for the development of self-learning machines that can adapt to varying external conditions.
- Non-volatile memory solutions for both binary and multilevel data storage
- Active switching elements in logic integrated circuits
- Plastic synapses that mimic neuronal functions in neuromorphic AI systems
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📰 Original Source: https://doi.org/10.33693/2313-223x-2025-12-4-20-28
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