Results 31 to 40 of about 65,516 (291)
, 2000 As already pointed out in Hardle, Klinke, and Muller (2000, Chapter 10), state-space models are very useful and flexible in the sense that various recursive methods for time-dependent situations can be formulated as general solutions of filtering, smoothing and prediction problems in state-space models.
openaire +3 more sources
Meniscus Pixel Printing for Contact‐Lens Vision Sensing and Robotic Control
Advanced Functional Materials, EarlyView.A visual‐sensing contact lens is enabled by meniscus pixel printing (MPP), which rapidly patterns a 200 µm perovskite photodetector pixel in 1 s without masks, vacuum processing, or bulky equipment. A deep‐learning‐based super‐resolution reconstructs sparse on‐lens signals into 80 × 80 high‐resolution visual information, while AI‐driven eye‐tracking ...
Byung‐Hoon Gong +7 more
wiley +1 more source
Sparsity-Based Kalman Filters for Data Assimilation [PDF]
, 2018 Several variations of the Kalman filter algorithm, such as the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), are widely used in science and engineering applications.
Kang, Wei, Xu, Liang
core +1 more source
A New Approach to Adaptive Signal Processing
, 2015 A unified linear algebraic approach to adaptive signal processing (ASP) is presented. Starting from just Ax=b, key ASP algorithms are derived in a simple, systematic, and integrated manner without requiring any background knowledge to the field ...
Anjum, Muhammad Ali Raza
core +2 more sources
Advanced Healthcare Materials, EarlyView.3D printed hybrid scaffolds combining bioactive silica–calcium chemistry with elastic polymers guide human bone stem cells to form bone. The scaffolds support cell survival, organization, and invasion while releasing osteogenic ions. Together, architecture and composition drive bone‐specific gene expression, extracellular matrix organization, and ...
David R. Sory +3 more
wiley +1 more source
Generalized Nonlinear Complementary Attitude Filter
, 2011 This work describes a family of attitude estimators that are based on a generalization of Mahony's nonlinear complementary filter. This generalization reveals the close mathematical relationship between the nonlinear complementary filter and the more ...
Jensen, Kenneth
core +1 more source
Advanced Robotics Research, EarlyView.Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek +3 more
wiley +1 more source
Austrian Journal of StatisticsThe problem of recursive filtering in linear state-space models is considered. The solution to this problem is the classical Kalman filter which is optimal in the sense that it minimizes the variance of the estimated states, if the error processes of ...
Bernhard Spangl
doaj +1 more source
Deep Kalman Filter: Simultaneous Multi-Sensor Integration and Modelling; A GNSS/IMU Case Study
Sensors, 2018 Bayes filters, such as the Kalman and particle filters, have been used in sensor fusion to integrate two sources of information and obtain the best estimate of unknowns. The efficient integration of multiple sensors requires deep knowledge of their error
Siavash Hosseinyalamdary
doaj +1 more source
Astrocyte Enrichment of 3D Cortical Constructs Enhances Brain Repair
Advanced Science, EarlyView.This study highlights the role of astrocytes in supporting neural progenitor cell survival and differentiation after traumatic brain injury. Astrocytes enhanced neuronal differentiation, improved cell survival in co‐cultures, and promoted integration of microfluidics‐based implants with host tissue following implantation. Additionally, increased axonal
Elisa M. Cruz +20 more
wiley +1 more source