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Memristor Circuits for Simulating Neuron Spiking and Burst Phenomena
Giacomo Innocenti1, Mauro Di Marco2, Alberto Tesi1
1Dipartimento di Ingegneria dell'Informazione, Università degli Studi di Firenze, Firenze, Italy.
Frontiers in Neuroscience
|June 28, 2021
Summary
Memristor circuits can mimic neuron dynamics by exploiting multistability. A novel pulse-programming method switches between circuit states, enabling simplified neuron response modeling.
Area of Science:
- Electronics
- Neuroscience
- Complex Systems
Background:
- Memristors are recognized for their synaptic applications in neuromorphic circuits.
- Mimicking neuronal dynamics is crucial for advanced artificial intelligence and brain-inspired computing.
Purpose of the Study:
- To demonstrate memristor circuits' capability in replicating neuronal dynamics.
- To leverage memristor circuit multistability and pulse-programming for neuron response emulation.
Main Methods:
- Utilizing a resistor-inductor-capacitor-memristor circuit exhibiting multistability (infinite attractors).
- Approximating limit cycles using the Describing Function (DF) method within Harmonic Balance (HB).
- Employing a pulse-programmed current source to switch between attractors, mimicking neuron responses.
Main Results:
- The memristor circuit demonstrated infinitely many stable equilibrium points and limit cycles.
- The Describing Function method provided analytical approximations for limit cycles.
- The memristor charge successfully mimicked simplified neuron models through controlled switching between states.
Conclusions:
- Memristor circuits, through multistability and pulse-programming, offer a viable platform for emulating neuronal dynamics.
- This approach provides a novel method for designing neuromorphic systems with neuron-like behavior.
- The DF method is effective for analyzing and designing such complex memristor-based circuits.
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