Single neurons in mouse sensorimotor cortex are organized by their activity features into distinct subpopulations with area-spanning footprints whose boundaries align closely with anatomical and ...
Abstract: In robotic manipulators, feedback control of nonlinear systems with fast finite-time convergence is desirable. However, because of the parametric and model uncertainties, the robust control ...
This paper is dedicated to the memory of my grandma. This is probably the only paper in my life that was written in a hospital the entire time. This is also at the same time the very first work in my ...
This demo shows how to train and test a human pose estimation using deep neural network. In R2019b, Deep Learning Toolbox(TM) supports low-level APIs to customize training loops and it enables us to ...
MATLAB could anchor the physical AI era, where simulation-first engineering and grounded generative AI turn physics into reliable, deployable intelligence. Recognize MATLAB as a vital tool in ...
A key challenge for systems neuroscience is to understand the coexistence of robustness and sensitivity in neural networks. In particular, a neural system must be robust against perturbations to its ...
Abstract: This paper presents a method for controlling the prosthetic leg using surface Electromyography (sEMG) signals, Artificial Neural Network (ANN), and Super Twisting Sliding Mode Control ...
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. In this eMag, we try to establish agentic AI ...
In order to analyse the sports psychology of athletes and to identify the psychology of athletes in their movements, a human action recognition (HAR) algorithm has been designed in this study. First, ...
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