Nanowerk

Atomic jitters power a new kind of probabilistic AI chip

Thermal noise in magnetic tunnel junctions, usually suppressed, now serves as a tunable source of randomness for Bayesian ...
Electronic Design

Selecting Minimum/Maximum Noise Frequencies for Transient Noise Simulation

Pinpointing the minimum and maximum transient noise bandwidth for a transient noise simulation is a non-trivial task. But ...
Control Global

Control strategies improve solar plant efficiency

Part three of this three-part series on justifying improved control via economics shows how simulation can quantify reduced ...
Scientific Research Publishing

Proposal for a Machine Learning Model to Improve Hauling Productivity in an Open-Pit Mine ()

This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within ...
BMJ Open

Association between epidural analgesia experience and future fertility intention in China: a national cross-sectional study

Objectives To assess the association between epidural analgesia (EDA) experience and subsequent fertility intention among ...
IEEE

Parameter Estimation and Modeling Performance of Compound-Gaussian Clutter with Weibull-Distributed Texture

Abstract: This paper addresses the parameter estimation of the compound-Gaussian clutter with Weibull distributed texture (CGWB). The CGWB distribution is introduced to model sea clutter, and it is ...
Investopedia

Trading Strategies Using Gaussian Statistical Models

Caroline Banton has 6+ years of experience as a writer of business and finance articles. She also writes biographies for Story Terrace. Carl Friedrich Gauss was a child prodigy and prominent ...
Scientific Research Publishing

KAN-Transformer Fusion with Mixture of Experts for Temporal Imputation of Spatiotemporal Air Pollution Data ()

The Kolmogorov-Arnold Network (abbr. KAN) is a novel neural network architecture inspired by the Kolmogorov-Arnold ...
IEEE

Power Flow Approximations for Multiphase Distribution Networks using Gaussian Processes

Abstract: Learning-based approaches are increasingly leveraged to manage and coordinate the operation of grid-edge resources in active power distribution networks. Among these, model-based techniques ...