Forgetting memristor based neuromorphic system for pattern training and recognition

A Memristor-based Neuromorphic Computing Application

Artificial neural networks have recently received renewed interest because of the discovery of the memristor. The memristor is the fourth basic circuit element, hypothesized to exist by Leon Chua in 1971 and physically realized in 2008. The two-terminal device acts like a resistor with memory and is therefore of great interest for use as a synapse in hardware ANNs. Recent advances in memristor ...

Memristor Pattern Recognition Circuit Architecture for Robotics

Pattern recognition solutions based on software are often limited by the speed of data transfer between memory and processor circuitry. Solutions based on application specific electronic hardware can be faster but are limited in adaptability to new patterns. These deficiencies in pattern recognition present a hurdle in further developing new applications in robotics. Last year researchers at HP...

Memristor - Based Analog Neuromorphic Computing Engine Design and Robust Training Scheme

A neuromorphic system for video object recognition

Automated video object recognition is a topic of emerging importance in both defense and civilian applications. This work describes an accurate and low-power neuromorphic architecture and system for real-time automated video object recognition. Our system, Neuormorphic Visual Understanding of Scenes (NEOVUS), is inspired by computational neuroscience models of feed-forward object detection and ...

CMOS and Memristor Technologies for Neuromorphic Computing Applications

In this work, I present a CMOS implementation of a neuromorphic system that aims to mimic the behavior of biological neurons and synapses in the human brain. The synapse is modeled with a memristor-resistor voltage divider, while the neuron-emulating circuit (“CMOS Neuron”) comprises transistors and capacitors. The input aggregation and output firing characteristics of a CMOS Neuron are based o...