Abstract: The present work focuses on the comprehensive implementation of gas/mixture identification employing chemometric analysis followed by on-chip realization. The chemometric analysis has been ...

Abstract: The conventional model reference adaptive system (MRAS) employs a proportional-integral (PI) controller with a low-pass filter (LPF). However, the LPF and integrator add phase delay and DC ...

It shows the schematic of the physics-informed neural network algorithm for pricing European options under the Heston model. The market price of risk is taken to be λ=0. Automatic differentiation is ...

Introduction: Underwater acoustic (UWA) communication systems confront significant challenges due to the unique, dynamic, and unpredictable nature of acoustic channels, which are impacted by low ...

Designed to accelerate advances in medicine and other fields, the tech giant’s quantum algorithm runs 13,000 times as fast as software written for a traditional supercomputer. A quantum computer at ...

Like clockwork, Apple has introduced a new M-series chip on updated versions of the iPad Pro, MacBook Pro and for the first time, Apple Vision Pro. The new M5 chip shares plenty of similarities with ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

Introduction: As the number of Internet of Things (IoT) devices grows quickly, cyber threats are becoming more complex and increasingly sophisticated; thus, we need a more robust network security ...

More than 800 U.S. TikTok users shared their data with The Washington Post. We used it to find out why some people become power users, spending hours per day scrolling. Each circle in the chart ...

In this important study, the authors model reinforcement-learning experiments using a recurrent neural network. The work examines if the detailed credit assignment necessary for back-propagation ...

Molecular circuits capable of autonomous learning could unlock novel applications in fields such as bioengineering and synthetic biology. To this end, existing chemical implementations of neural ...