Memristive Complex Functions for Design of Deep Neural Network Page 1 Ivan Kipelkin
Lobachevsky State University Nizhniy Novgorod, Russia Ivan.kipelkin@yandex.ru Svetlana …

As an important part of memory, memristor-based neural networks of memory are seldom
involved in long-term memory. In this paper, a memristor-based neural network of long-term …

This chapter covers the implementation of deep learning neural networks and memristive
systems. In particular, deep memristive convolutional neural network (CNN) implementation …

In this paper, a fully circuit implementation of Memristive Neural Network (MNN) is proposed.
The forward calculation of the network is based on winner-take-all (WTA) mechanism. The …

A generalized bell-shaped function is an essential building block for a neuro-fuzzy systems
and radial basis function neural networks. With the advent of edge computing, analog neuro …

Convolutional neural networks exhibit state-of-the-art performance in many image
recognition tasks. Their software implementation on computers with von Neumann …

It improves the data processing performance and efficiency notably that the memristor-based
neuromorphic system is constructed by mimicking the features of brain. This paper proposes …

The definition of a memristor was introduced by Professor LO Chua in 1971. By generalizing
the definition of a memristor, memristive devices and systems were also proposed. Since the …

Artificial neural network (NN) circuits are proposed and analyzed from the viewpoints of
flexibility and robustness based on memristive devices. The typical 3-layered fully …

Recent implementations of memristors have opened up the possibility of making brain-like
artificial intelligence neuromorphic computing systems, including highly scalable and low …