ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024
Mechanical Neural Networks with Explicit and Robust Neurons.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- A Physical Adaptive Material Motor Unit Neural Network: A Hygromorph Composite Material Machine.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Reprogrammable metamaterial robot with embodied versatile computation and mechanical intelligence.Nature communications · 2026Article
- Programmable Metamaterials with Perforated Shell Group Supporting Versatile Information Processing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Article
- Mechanical Neural Networks with Explicit and Robust Neurons.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Mechanical computing provides an information processing method to realize sensing-analyzing-actuation integrated mechanical intelligence and, when combined with neural networks, can be more efficient for data-rich cognitive tasks. The requirement of solving implicit and usually nonlinear equilibrium equations of motion in training mechanical neural networks makes computation challenging and costly. Here, an explicit mechanical neuron is developed of which the response can be directly determined without the need of solving equilibrium equations. A training method is proposed to ensure the robustness of the neuron, i.e., insensitivity to defects and perturbations. The explicitness and robustness of the neurons facilitate the assembly of various network structures. Two exemplified networks, a robust mechanical convolutional neural network and a mechanical recurrent neural network with long short-term memory capabilities for associative learning, are experimentally demonstrated. The introduction of the explicit and robust mechanical neuron streamlines the design of mechanical neural networks fulfilling robotic matter with a level of intelligence.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.