Abstract: This paper presents a new method for enhancing Alternating Current Power Flow (ACPF) analysis. The method integrates the Newton-Raphson (NR) method with Enhanced-Gradient Descent (GD) and ...
Abstract: This letter introduces the design of a novel broadband subharmonic mixer operating at 220–330 GHz, which can be applied in the fields of spectrum analysis and wireless communication systems.
Abstract: This study presents an approach for multi-drone path planning in warehouse environments using a combination of the Gradient Descent Method and Artificial Potential Fields (APF). The ...
Y Combinator CEO Garry Tan praised Anthropic's new AI coding tool, Claude Code Claude Code operates in the terminal, managing codebase tasks using natural language. AI tools like Claude Code are ...
Abstract: Factor graphs are fundamental to large-scale estimation in robotics and computer vision, but their underlying normal equations incur significant computational costs. To overcome this, we ...
Abstract: Distributed weakly convex optimization is a significant class of problems in signal and information processing, with wide-ranging applications such as sparse dictionary learning, low-rank ...
Create a clear water drop drawing that looks so realistic it feels like you could touch it. In this tutorial, you will learn how to draw a transparent water droplet using simple steps that build ...
Abstract: This article presents a method that integrates direction-of-arrival (DoA) estimation with low probability of intercept (LPI) based on a space-time-modulated metasurface (STM-MTS). The ...
Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient Descent is an algorithm we use to minimize the cost function value, so as to ...
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