Results 191 to 200 of about 782,529 (256)

Uncontrolled Learning: Codesign of Neuromorphic Hardware Topology for Neuromorphic Algorithms

Advanced Intelligent Systems, EarlyView.
Codesign is used to implement a neuroscience‐inspired machine learning algorithm in all neuromorphic hardware. In this implementation, the hidden memristors cannot be directly accessed, limiting control of the network during training. By leveraging theoretical tools, including memristor circuits dynamics and a closed form expression for the network ...
Frank Barrows, Jonathan Lin, Francesco Caravelli, Dante R. Chialvo   +3 more
wiley   +1 more source

Deep Q‐Network‐Based Hierarchical Path Planning of a Biped Wall‐Climbing Robot for Window Cleaning

Advanced Intelligent Systems, EarlyView.
This article presents a biped wall‐cleaning climbing robotic system for the maintenance of multi‐isolated areas on exoskeleton‐structured windows (ESWs). A full coverage cleaning approach is proposed by integrating a deep Q‐network‐based method with the robotic system to address the complete coverage cleaning path planning problem.
Weijian Zhang, Zikang Li, Lap Mou Tam, Qingsong Xu   +3 more
wiley   +1 more source

M 115.00C: Probability and Linear Mathematics [PDF]

, 2016
Unknown,
core   +1 more source

Artificial Intelligence‐Enhanced, Closed‐Loop Wearable Systems Toward Next‐Generation Diabetes Management

Advanced Intelligent Systems, EarlyView.
Recent advancements in wearable healthcare have brought accessible continuous glucose monitoring systems (CGMs) for diabetes management. To address the limitations of CGMs, closed‐loop systems utilizing monitored glucose levels for insulin dosing are being developed.
Wei Huang, Ivo Pang, Jing Bai, Binbin Cui, Xiaojuan Qi, Shiming Zhang   +5 more
wiley   +1 more source

M 115.10: Probability and Linear Mathematics [PDF]

, 2018
Fern, Lauren S.
core   +1 more source

UP3: Unsupervised Predictive Path Planner for Mobile Robots in Unknown Environment

Advanced Intelligent Systems, EarlyView.
In this article, an unsupervised learning‐based predictive path planning framework UP3 for mobile robots is introduced. The framework employs attention‐based path optimization, control barrier functions, and a deep constraint correction module. UP3 allows the robot to use local observation to generate smooth, safe, and collision‐free path points toward
Jianing Luo, Jiwei Zhu, Ruopeng Cui, Gaoxiong Lu, Wei Li   +4 more
wiley   +1 more source

MATHEMATICAL ANALYSIS OF A FEW MIGRATORY FLOW MODELS WITH ENDOGENEOUS MIGRATION PROBABILITY

, 2013
Manuel Philippe Émile Garçon
openalex   +1 more source

MATH 117.03: Probability and Linear Mathematics [PDF]

, 2000
Stroethoff, Karel M.
core   +1 more source

Applied Artificial Intelligence in Materials Science and Material Design

Advanced Intelligent Systems, EarlyView.
AI‐driven methods are transforming materials science by accelerating material discovery, design, and analysis, leveraging large datasets to enhance predictive modeling and streamline experimental techniques. This review highlights advancements in AI applications across spectroscopy, microscopy, and molecular design, enabling efficient material ...
Emigdio Chávez‐Angel, Martin Børstad Eriksen, Alejandro Castro‐Alvarez, Jose H. Garcia, Marc Botifoll, Oscar Avalos‐Ovando, Jordi Arbiol, Aitor Mugarza   +7 more
wiley   +1 more source

GACNet: Interactive Prediction of Surrounding Vehicles Behavior under High Collision Risk

Advanced Intelligent Systems, EarlyView.
This study designs a dual‐stage prediction framework and introduces a conflict analysis module. This module refines the initially predicted future trajectories and performs collision detection and behavior analysis on the refined trajectories, thereby learning the true interactive behaviors of multiple agents in high‐collision‐risk scenarios.
Jingzheng Chai, Jianting Liu, Jingluo Huang, Chunyan Huang   +3 more
wiley   +1 more source