Simulating Memristor Crossbar Array and Spiking Neural Network Interactions for Insight into System Dynamics

In this C64 program, we will simulate a memristor crossbar array along with a simple spiking neural network. The purpose of this simulation is to automatically simulate changes in the crossbar array by randomly setting some memristors to 1. When a memristor is set to 1, the corresponding neuron in the neural network will spike.

At the beginning of each iteration, the program will randomly select some memristors and set them to 1. This step mimics the changes that occur naturally in a real crossbar array.

After setting the memristors, the program will check if any memristor is set to 1. If a memristor is found, the corresponding neuron in the neural network will spike. This spike represents the activation of the neuron due to the change in the crossbar array.

Once all the spikes have been processed, the program will display the current state of both the crossbar array and the neurons. This step allows us to observe the changes and patterns that occur in the simulation.

The neural network in this simulation consists of three neurons. At the end of each iteration, their states will be reset to ensure a fresh start for the next iteration.

The simulation will run for a total of 1000 iterations. During this time, we will be able to observe the evolution of the crossbar array and the behavior of the neurons.

Through this program, we aim to gain insights into the dynamics of a memristor crossbar array and its influence on a simple spiking neural network. By simulating these interactions, we can better start to understand the potential applications and behaviors of these systems.

Links(rename in .bas for the compiler)