Journal ArticleDOI
Experimental Demonstration of Feature Extraction and Dimensionality Reduction Using Memristor Networks
TLDR
It is experimentally demonstrated that memristor arrays can be used to perform principal component analysis, one of the most commonly used feature extraction techniques, through online, unsupervised learning.Abstract:
Memristors have been considered as a leading candidate for a number of critical applications ranging from nonvolatile memory to non-Von Neumann computing systems. Feature extraction, which aims to transform input data from a high-dimensional space to a space with fewer dimensions, is an important technique widely used in machine learning and pattern recognition applications. Here, we experimentally demonstrate that memristor arrays can be used to perform principal component analysis, one of the most commonly used feature extraction techniques, through online, unsupervised learning. Using Sanger’s rule, that is, the generalized Hebbian algorithm, the principal components were obtained as the memristor conductances in the network after training. The network was then used to analyze sensory data from a standard breast cancer screening database with high classification success rate (97.1%).read more
Citations
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Journal ArticleDOI
The future of electronics based on memristive systems
TL;DR: The state of the art in memristor-based electronics is evaluated and the future development of such devices in on-chip memory, biologically inspired computing and general-purpose in-memory computing is explored.
Journal ArticleDOI
Analogue signal and image processing with large memristor crossbars
Can Li,Miao Hu,Miao Hu,Yunning Li,Hao Jiang,Ning Ge,Eric Montgomery,Jiaming Zhang,Wenhao Song,Noraica Davila,Catherine Graves,Zhiyong Li,John Paul Strachan,Peng Lin,Zhongrui Wang,Mark Barnell,Qing Wu,R. Stanley Williams,Jianhua Yang,Qiangfei Xia +19 more
TL;DR: It is shown that reconfigurable memristor crossbars composed of hafnium oxide memristors on top of metal-oxide-semiconductor transistors are capable of analogue vector-matrix multiplication with array sizes of up to 128 × 64 cells.
Journal ArticleDOI
Efficient and self-adaptive in-situ learning in multilayer memristor neural networks
Can Li,Daniel Belkin,Daniel Belkin,Yunning Li,Peng Yan,Peng Yan,Miao Hu,Miao Hu,Ning Ge,Hao Jiang,Eric Montgomery,Peng Lin,Zhongrui Wang,Wenhao Song,John Paul Strachan,Mark Barnell,Qing Wu,R. Stanley Williams,Jianhua Yang,Qiangfei Xia +19 more
TL;DR: This work monolithically integrate hafnium oxide-based memristors with a foundry-made transistor array into a multiple-layer memristor neural network and achieves competitive classification accuracy on a standard machine learning dataset.
Journal ArticleDOI
Resistive switching materials for information processing
Zhongrui Wang,Huaqiang Wu,Geoffrey W. Burr,Cheol Seong Hwang,Kang L. Wang,Qiangfei Xia,Jianhua Yang +6 more
TL;DR: This Review surveys the four physical mechanisms that lead to resistive switching materials enable novel, in-memory information processing, which may resolve the von Neumann bottleneck and examines the device requirements for systems based on RSMs.
Journal ArticleDOI
A fully integrated reprogrammable memristor–CMOS system for efficient multiply–accumulate operations
Fuxi Cai,Justin M. Correll,Seung Hwan Lee,Yong Lim,Yong Lim,Vishishtha Bothra,Zhengya Zhang,Michael P. Flynn,Wei Lu +8 more
TL;DR: A programmable neuromorphic computing chip based on passive memristor crossbar arrays integrated with analogue and digital components and an on-chip processor enables the implementation of neuromorphic and machine learning algorithms.
References
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Journal ArticleDOI
Pattern Recognition and Machine Learning
TL;DR: This book covers a broad range of topics for regular factorial designs and presents all of the material in very mathematical fashion and will surely become an invaluable resource for researchers and graduate students doing research in the design of factorial experiments.
Journal ArticleDOI
The missing memristor found
TL;DR: It is shown, using a simple analytical example, that memristance arises naturally in nanoscale systems in which solid-state electronic and ionic transport are coupled under an external bias voltage.
Book
Image Processing: Analysis and Machine Vision
TL;DR: The digitized image and its properties are studied, including shape representation and description, and linear discrete image transforms, and texture analysis.
Journal ArticleDOI
Cellular neural networks: theory
Leon O. Chua,L. Yang +1 more
TL;DR: In this article, a class of information processing systems called cellular neural networks (CNNs) are proposed, which consist of a massive aggregate of regularly spaced circuit clones, called cells, which communicate with each other directly through their nearest neighbors.
Journal ArticleDOI
Nanoscale Memristor Device as Synapse in Neuromorphic Systems
TL;DR: A nanoscale silicon-based memristor device is experimentally demonstrated and it is shown that a hybrid system composed of complementary metal-oxide semiconductor neurons and Memristor synapses can support important synaptic functions such as spike timing dependent plasticity.