Surface-shaping mechatronic neural network
Surface-shaping mechatronic neural network

Author(s): Dobri Komarski, Velizar Vassilev, Hristiana Nikolova
Subject(s): Economy, Business Economy / Management, Accounting - Business Administration, Business Ethics
Published by: Национално издателство за образование и наука „Аз-буки“
Keywords: mechatronic; neural network; flexure; rotation; surface-shape; parallel kinematic
Summary/Abstract: Neural networks are fundamental concept in artificial intelligence and machine learning, inspired by the structure and function of the human brain. A neural network is a computational model composed of interconnected nodes (called neurons or units) organized in layers. These networks are designed to recognize patterns, learn from data, and make predictions or decisions. As a part of the neural networks, mechanical neural networks are physical systems designed to mimic the behavior of artificial neural networks using mechanical components. These systems leverage the properties of materials and structures to process information, adapt to external stimuli, or perform tasks such as pattern recognition, optimization, or control. The developed surface-shaping mechanical neural network is based on systems with parallel kinematics but in addition contains sensing elements part of the electronic system controlled by developed software. The system can adapt its surface geometry depend on the external stimuli, in this case the force applied on it.

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