In this paper, a new design procedure has been proposed for realization of logarithmic function via three phases: 1) differentiation; 2) division; and 3) integration for any arbitrary analog signal.

SinkhornAutoDiff - Python toolbox to integrate optimal transport loss functions using automatic differentiation and Sinkhorn's algorithm Overview Python toolbox to compute and differentiate Optimal ...

The hardware computation of the logarithm function is required in several applications, ranging from signal and image processing to telecommunication systems. This brief shows that most of previous ...

Binance, the largest cryptocurrency exchange in the world by trading volume and users, has released a set of AI-powered token analysis tools aimed at making ...

What about coding a Spiking Neural Network using an automatic differentiation framework? In SNNs, there is a time axis and the neural network sees data throughout time, and activation functions are ...

It's said that the Romans first devised a hand gesture that served as a sign of formal respect for a military officer. In the Middle Ages, this signal was adapted to help differentiate between friend ...

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Applied Computational Psychiatry Lab, Mental Health Neuroscience Department, Division of Psychiatry and Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Department of Imaging ...

The world’s top supply chains aren’t just optimizing for cost or efficiency anymore—they’re redefining the very purpose of ...

New research shows that an adrenaline-binding protein on T cells acts as a timekeeper for the cells’ infection-fighting ...

The camera rumors are flying thick and fast! Here are the most credible rumblings and reports about what's coming next ...