This article explains the principles and applications of continuous-time sigma-delta ADCs, while comparing their advantages and disadvantages with discrete-time versions. Sigma-delta analog-to-digital ...
Abstract: Networked control systems have received increasing attention from many communities over the recent decades, and the use of network devices with limited capacities brings significant ...
Abstract: In this paper, motivated by human neurocognitive experiments, a model-free off-policy reinforcement learning algorithm is developed to solve the optimal tracking control of multiple-model ...
Principal Data Engineer Rajesh Mattaparthi is using transformer-based AI to detect hidden faults in standby power generators ...
Two interesting articles were presented in this newspaper several weeks ago about the apparent shift toward analog technology. While this show of nostalgia is refreshing to see, equally so is the ...
Aerospace and Mechanical Insider on MSN

Multi-agent reinforcement learning driving smart factory agility

At the core of Industry 4.0, the smart factory integrates automation, mass customization, and self-organization into a highly ...
Most AI transformations aim to generate value, not to learn. The most durable advantage comes from designing learning into ...
Force limiting, formally called PFL, is a core safety mechanism in collaborative robotics. It ensures a robot’s applied force ...
The loop takes agentic AI a step further, by authorizing a swarm of agents to work continuously in the background, endlessly.
The New York Knicks have restored the feeling. So here's the 100 best New York City rap songs of all time, with classics from ...
Regulators require organizations to create and retain records because documentation makes compliance visible. Recordkeeping ...