Results 71 to 80 of about 70,734 (340)

Compliant Pneumatic Feet with Real‐Time Stiffness Adaptation for Humanoid Locomotion

Advanced Robotics Research, EarlyView.
A compliant pneumatic foot with real‐time variable stiffness enables humanoid robots to adapt to changing terrains. Using onboard vision and pressure control, the foot modulates stiffness within each gait cycle, reducing impact forces and improving balance. The design, cast in soft silicone with embedded air chambers and Kevlar wrapping, offers durable,
Irene Frizza, Hiroshi Kaminaga, Philippe Fraisse, Gentiane Venture   +3 more
wiley   +1 more source

Hierarchical Summary Statistics Encoding Across Primary Visual and Posterior Parietal Cortices

Advanced Science, EarlyView.
This study shows that mouse V1 simultaneously encodes the ensemble mean and variance of motion, providing a robust summary‐statistic representation that persists despite single‐neuron variability. These signals propagate to PPC, where they are transformed into abstract category representations during decision making.
Young‐Beom Lee, Oliver James, Gaeun Jung, Doyun Lee, Yee‐Joon Kim   +4 more
wiley   +1 more source

Bayesian Compressive Sensing as Applied to Directions-of-Arrival Estimation in Planar Arrays

Journal of Electrical and Computer Engineering, 2013
The Bayesian compressive sensing (BCS) is applied to estimate the directions of arrival (DoAs) of narrow-band electromagnetic signals impinging on planar antenna arrangements.
Matteo Carlin, Paolo Rocca, Giacomo Oliveri, Andrea Massa   +3 more
doaj   +1 more source

From Denoising to Compressed Sensing

, 2016
A denoising algorithm seeks to remove noise, errors, or perturbations from a signal. Extensive research has been devoted to this arena over the last several decades, and as a result, today's denoisers can effectively remove large amounts of additive ...
Baraniuk, Richard G., Maleki, Arian, Metzler, Christopher A.   +2 more
core   +1 more source

Dynamic Mode Decomposition for Compressive System Identification [PDF]

, 2020
Dynamic mode decomposition has emerged as a leading technique to identify spatiotemporal coherent structures from high-dimensional data, benefiting from a strong connection to nonlinear dynamical systems via the Koopman operator.
Bai, Zhe, Brunton, Steven L, Kaiser, Eurika, Kutz, J Nathan, Proctor, Joshua L   +4 more
core  

Bayesian Compressed Sensing with Heterogeneous Side Information [PDF]

2016 Data Compression Conference (DCC), 2016
The classical compressed sensing (CS) paradigm can be modified so as to leverage a signal correlated to the signal of interest, called side information, which is assumed to be provided a priori at the decoder in order to aid reconstruction. In this work, we propose a novel CS reconstruction method based on belief propagation principles, which manages ...
Zimos, Evangelos, Mota, Joao, Rodrigues, Miguel, Deligiannis, Nikolaos   +3 more
openaire   +2 more sources

Machine‐Learning Microfluidic Minute‐Scale Microorganism Metrics Monitoring(M6)

Advanced Science, EarlyView.
ABSTRACT On‐site monitoring of microorganisms remains challenging because of low concentrations, strong background interference, and dynamic aerosol diffusion, particularly for aerosol‐transmitted pathogens. Here, we report a rapid detection platform that integrates a Puri‐focusing microfluidic chip, electrochemical impedance spectroscopy (EIS), and ...
Ning Yang, Jiahao Ding, Si Chen, Lijie Yan, Shichao Ding, Lavonda Li, Junyi Sun, Haodong Liu, Tongge Li, Ning Liu, Mingji Wei, Xiaoyong Zhu, Xiaobo Zou, Shouqi Yuan, Xingcai Zhang   +14 more
wiley   +1 more source

Sample Distortion for Compressed Imaging

, 2013
We propose the notion of a sample distortion (SD) function for independent and identically distributed (i.i.d) compressive distributions to fundamentally quantify the achievable reconstruction performance of compressed sensing for certain encoder-decoder
Davies, Mike E., Guo, Chunli
core   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Exploiting Fine-Grained Subcarrier Information for Device-Free Localization in Wireless Sensor Networks

Sensors, 2018
Device-free localization (DFL) that aims to localize targets without carrying any electronic devices is addressed as an emerging and promising research topic.
Yan Guo, Dongping Yu, Ning Li
doaj   +1 more source