An electromagnetic perspective of artificial intelligence neuromorphic chips
The emergence of artificial intelligence has represented great potential in solving a wide
range of complex problems. However, traditional general-purpose chips based on von …
range of complex problems. However, traditional general-purpose chips based on von …
Recent progress on signal integrity modeling of neuromorphic chips by the PEEC method
With the rapid advances of artificial intelligence and its applications, the design of memristor-
based neuromorphic chips inspired by the human brain has become an important area of …
based neuromorphic chips inspired by the human brain has become an important area of …
S‐parameter extraction for electromagnetic modelling of memristor‐based crossbar array circuits
This article presents an efficient S‐parameter extraction method for memristor‐based
crossbar array circuits. The proposed approach involves converting the array into an …
crossbar array circuits. The proposed approach involves converting the array into an …
Image and Audio Data Classification Using Bagging Ensembles of Spiking Neural Networks with Memristive Plasticity
Spiking neural networks (SNNs) are potentially capable of greatly reducing the energy
requirements of modern intelligent systems when combined with neuromorphic computing …
requirements of modern intelligent systems when combined with neuromorphic computing …
Latency Insertion Method for Accelerated Simulation of Memristor Crossbar Array in Neuromorphic Chip
Neuromorphic chips constructed by memristor crossbar array have been introduced to
realize in-memory computation. The simulations are usually conducted by full-wave …
realize in-memory computation. The simulations are usually conducted by full-wave …