Generalize Hopfield-like neural networks using a deformed maximum entropy principle. Exhibit explosive transitions, multi-stability, and memory capacity enhancements. Are analytically tractable via ...

When you write your name in the air, you can see the letters appear on your smartphone. By Cade Metz Reporting from San Francisco The prototype looks like a giant rectangular wristwatch. But it ...

We manipulate the structure of an artificial neural network to isolate the influence of anatomical architecture on the emergence of the topological gradient of activation pattern propagation observed ...

Abstract: In modern era, Multiple Input Multiple Output (MIMO) technology is a crucial element in wireless technology, where accurate prediction of Channel State Information (CSI) feedback is critical ...

Abstract: In spiking neural networks (SNNs), the main unit of information processing is the neuron with an internal state. The internal state generates an output spike based on its component ...

Quantum convolutional neural networks (QCNNs) represent a promising approach in quantum machine learning, paving new directions for both quantum and classical data analysis. This approach is ...

Institute of high energy physics, Chinese academy of sciences, Beijing 100049, China University of Chinese Academy of Sciences, Beijing 100049, China ...

This page describes design iterations from basic C code to working FPGA implementation of a simple single layer neural net inference computation (MNIST). This is meant to be an easy to understand demo ...

From the micromixer topology by Barrie Gilbert [1], this amplifier allows a single-ended input to be converted to a Class A/B current output from a single supply. Wow the engineering world with your ...