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Experimental demonstration of spatiotemporal analog computation in ultrafast optics [PDF]

Light: Science & Applications
It is intractable to perform information processing and computation on single ultrafast optical pulses, within picoseconds or even femtoseconds. Here, we experimentally demonstrate an optical spatiotemporal differentiator, a mirror-symmetry-breaking ...
Junyi Huang, Dong Zhao, Jixuan Shi, Hongliang Zhang, Hengyi Wang, Fang-Wen Sun, Qiwen Zhan, Shiyao Zhu, Kun Huang, Zhichao Ruan   +9 more
doaj   +2 more sources

Four-Analog Computation Based on DNA Strand Displacement [PDF]

ACS Omega, 2017
Chengye Zou, Xiaopeng Wei, Qiang Zhang, Chanjuan Liu, Changjun Zhou, Yuan Liu   +5 more
doaj   +2 more sources

How (and why) to think that the brain is literally a computer

Frontiers in Computer Science, 2022
The relationship between brains and computers is often taken to be merely metaphorical. However, genuine computational systems can be implemented in virtually any media; thus, one can take seriously the view that brains literally compute.
Corey J. Maley
doaj   +1 more source

Using Biochemical Circuits to Approximately Compute Log-Likelihood Ratio for Detecting Persistent Signals

IEEE Access, 2021
Given that biochemical circuits can process information by using analog computation, a question is: What can biochemical circuits compute? This paper considers the problem of using biochemical circuits to distinguish persistent signals from transient ...
Chun Tung Chou
doaj   +1 more source

The computational power of the human brain

Frontiers in Cellular Neuroscience, 2023
At the end of the 20th century, analog systems in computer science have been widely replaced by digital systems due to their higher computing power. Nevertheless, the question keeps being intriguing until now: is the brain analog or digital?
Peter J. Gebicke-Haerter
doaj   +1 more source

Consumer Document Analytical Accelerator Hardware

IEEE Access, 2023
Document scanning devices are used for visual character recognition, followed by text analytics in the software. Often such character extraction is insecure, and any third party can manipulate the information.
Aswani Radhakrishnan, Dibyasha Mahapatra, Alex James   +2 more
doaj   +1 more source

Training of Mixed-Signal Optical Convolutional Neural Networks With Reduced Quantization Levels

IEEE Access, 2021
Analog computing paradigms are promising solutions to the growing computational demands of machine learning applications. Despite being susceptible to errors, analog and mixed-signal platforms have the potential to achieve higher speed and power ...
Zheyuan Zhu, Joseph Ulseth, Guifang Li, Shuo Pang   +3 more
doaj   +1 more source

Analog monolayer SWCNTs-based memristive 2D structure for energy-efficient deep learning in spiking neural networks

Scientific Reports, 2023
Advances in materials science and memory devices work in tandem for the evolution of Artificial Intelligence systems. Energy-efficient computation is the ultimate goal of emerging memristor technology, in which the storage and computation can be done in ...
Heba Abunahla, Yawar Abbas, Anteneh Gebregiorgis, Waqas Waheed, Baker Mohammad, Said Hamdioui, Anas Alazzam, Moh’d Rezeq   +7 more
doaj   +1 more source

A Software-Circuit-Device Co-Optimization Framework for Neuromorphic Inference Circuits

IEEE Access, 2022
Neuromorphic circuits, which usually use analog computation for vector-matrix multiplication (VMM) in neural networks (NN), are promising machine learning accelerators with much lower latency and power consumption than digital ones. Analog computation is
Paul Quibuyen, Tom Jiao, Hiu Yung Wong
doaj   +1 more source

Memristors for the Curious Outsiders

Technologies, 2018
We present both an overview and a perspective of recent experimental advances and proposed new approaches to performing computation using memristors.
Francesco Caravelli, Juan Pablo Carbajal   +1 more
doaj   +1 more source