Memristor

Memory analysis for memristors and memristive recurrent neural networks

Traditional recurrent neural networks are composed of capacitors, inductors, resistors, and operational amplifiers. Memristive neural networks are constructed by replacing resistors with memristors. This paper focuses on the memory analysis, i.e. the …

Exponential adaptive lag synchronization of memristive neural networks via fuzzy method and applications in pseudo random number generators

This paper investigates the problem of exponential lag synchronization control of memristive neural networks (MNNs) via the fuzzy method and applications in pseudorandom number generators. Based on the knowledge of memristor and recurrent neural …

Implementation of memristive neural networks with spike-rate-dependent plasticity synapse

The property of changing resistance according to applied currents of memristors makes them candidates for emulating synapses in artificial neural networks. In this paper, we introduce a memristive synapse design into neural network circuits. Combined …