Results 71 to 80 of about 14,001 (185)

Recent Developments on Novel 2D Materials for Emerging Neuromorphic Computing Devices

Small Structures
The rapid advancement of artificial intelligent and information technology has led to a critical need for extremely low power consumption and excellent efficiency.
Muhammad Hamza Pervez, Ehsan Elahi, Muhammad Asghar Khan, Muhammad Nasim, Muhammad Asim, Arslan Rehmat, Malik Abdul Rehman, Mohammed A. Assiri, Shania Rehman, Jonghwa Eom, Muhammad Farooq Khan   +10 more
doaj   +1 more source

Neuromorphic In-Memory Computing Framework using Memtransistor Cross-bar based Support Vector Machines

, 2019
This paper presents a novel framework for designing support vector machines (SVMs), which does not impose restriction on the SVM kernel to be positive-definite and allows the user to define memory constraint in terms of fixed template vectors. This makes
Chakrabartty, S., Chatterjee, O., Ghosh, A., Kumar, P., Nair, A. R., Paul, T., Thakur, C. S.   +6 more
core   +1 more source

Low-Power Microwave Relaxation Oscillators Based on Phase-Change Oxides for Neuromorphic Computing

Physical Review Applied, 2019
Neuromorphic computing is an efficient solution for large-scale associative learning problems such as pattern recognition, but its hardware implementation is stymied by the need for low-power, scalable faux neurons, typically built using relaxation oscillators.
B. Zhao, J. Ravichandran
openaire   +2 more sources

Electrolyte Gated Transistors for Brain Inspired Neuromorphic Computing and Perception Applications: A Review

Nanomaterials
Emerging neuromorphic computing offers a promising and energy-efficient approach to developing advanced intelligent systems by mimicking the information processing modes of the human brain.
Weisheng Wang, Liqiang Zhu
doaj   +1 more source

Towards Accurate and High-Speed Spiking Neuromorphic Systems with Data Quantization-Aware Deep Networks

, 2019
Deep Neural Networks (DNNs) have gained immense success in cognitive applications and greatly pushed today's artificial intelligence forward. The biggest challenge in executing DNNs is their extremely data-extensive computations. The computing efficiency
Liu, C., Liu, Fuqiang
core   +1 more source

TraNNsformer: Neural network transformation for memristive crossbar based neuromorphic system design

, 2017
Implementation of Neuromorphic Systems using post Complementary Metal-Oxide-Semiconductor (CMOS) technology based Memristive Crossbar Array (MCA) has emerged as a promising solution to enable low-power acceleration of neural networks. However, the recent
Ankit, Aayush, Roy, Kaushik, Sengupta, Abhronil   +2 more
core   +1 more source

Preparation of MXene-based hybrids and their application in neuromorphic devices

International Journal of Extreme Manufacturing
The traditional von Neumann computing architecture has relatively-low information processing speed and high power consumption, making it difficult to meet the computing needs of artificial intelligence (AI). Neuromorphic computing systems, with massively
Zhuohao Xiao, Xiaodong Xiao, Ling Bing Kong, Hongbo Dong, Xiuying Li, Bin He, Shuangchen Ruan, Jianpang Zhai, Kun Zhou, Qin Huang, Liang Chu   +10 more
doaj   +1 more source

A neuromorphic systems approach to in-memory computing with non-ideal memristive devices: From mitigation to exploitation

, 2018
Memristive devices represent a promising technology for building neuromorphic electronic systems. In addition to their compactness and non-volatility features, they are characterized by computationally relevant physical properties, such as state ...
Indiveri, Giacomo, Muller, Lorenz K., Nair, Manu V, Payvand, Melika   +3 more
core   +1 more source

Highly Scalable Neuromorphic Hardware with 1-bit Stochastic nano-Synapses

, 2013
Thermodynamic-driven filament formation in redox-based resistive memory and the impact of thermal fluctuations on switching probability of emerging magnetic switches are probabilistic phenomena in nature, and thus, processes of binary switching in these ...
Kavehei, Omid, Skafidas, Efstratios
core   +1 more source

A Review of Nanowire Devices Applied in Simulating Neuromorphic Computing

Nanomaterials
With the rapid advancement of artificial intelligence and machine learning technologies, the demand for enhanced device computing capabilities has significantly increased.
Tianci Huang, Yuxuan Wang, Zhihan Jin, Hao Liu, Kaili Wang, Tan Leong Chee, Yi Shi, Shancheng Yan   +7 more
doaj   +1 more source