Results 51 to 60 of about 26,219 (311)
Full‐Stack Architectures for Intelligent Brain‐Computer Interfaces
Advanced Science, EarlyView.System‐level overview of brain–computer interfaces (BCIs), illustrating the integration of neural signal acquisition, wireless transmission, and adaptive decoding. Advanced electrode, tissue interfaces, energy‐efficient communication, and robust algorithms collectively enable stable signal quality, real‐time processing, and closed‐loop operation ...
Hee Kyu Lee +9 more
wiley +1 more source
Square root kalman filter with contaminated observations [PDF]
, 1992 The algorithm of square root Kalman filtering for the case of contaminated observations is described in the paper. This algorithm is suitable for the parallel computer implementation allowing to treat dynamic linear systems with large number of state ...
Rubio, A., Romera, Rosario, Cipra, Tomas
core
, 2013 Publication in the conference proceedings of EUSIPCO, Marrakech, Morocco ...
Subhro Das, José M. F. Moura
openaire +3 more sources
Terahertz Channel Modeling, Estimation and Localization in RIS‐Assisted Systems
Advanced Electronic Materials, EarlyView.Reconfigurable intelligent surfaces have become a recent intensive research focus. Based on practical applications, channel strategies for RIS‐assisted terahertz wireless communication systems are categorized into three different types: channel modeling, channel estimation, and channel localization.
Hongjing Wang +9 more
wiley +1 more source
On Kalman Filtering with Nonlinear Equality Constraints
, 2007 The state space description of some physical systems possess nonlinear equality constraints between some state variables. In this paper, we consider the problem of applying a Kalman filter-type estimator in the presence of such constraints. We categorize
Julier, SJ +3 more
core +1 more source
Advanced Electronic Materials, EarlyView.In dynamic driving scenarios, the proposed approach ensures only temporally aligned sensor inputs to make driving decisions, preventing false activations. By enabling selective hardware‐level learning, it achieves fast, reliable responses under noisy conditions.
Kapil Bhardwaj +4 more
wiley +1 more source
Boundary Value Problems Arising in Kalman Filtering
Boundary Value Problems, 2009 The classic Kalman filtering equations for independent and correlated white noises are ordinary differential equations (deterministic or stochastic) with the respective initial conditions.
Sinem Ertürk +2 more
doaj +1 more source
Attitude Estimation Algorithm of Portable Mobile Robot Based on Complementary Filter
Micromachines, 2021 In robot inertial navigation systems, to deal with the problems of drift and noise in the gyroscope and accelerometer and the high computational cost when using extended Kalman filter (EKF) and particle filter (PF), a complementary filtering algorithm is
Mei Liu +3 more
doaj +1 more source
AIChE Journal, EarlyView.ABSTRACT Hybrid modeling combines first‐principles equations with a data‐driven subcomponent. Training for the data‐driven part is sensitive to measurement noise when training targets are constructed using pointwise time derivatives. Beyond differentiation errors, hybrid models involve solving an inverse problem to estimate the data‐driven term, which ...
Hangjun Cho +4 more
wiley +1 more source
An Adaptive Unscented Kalman Filtering Algorithm for MEMS/GPS Integrated Navigation Systems
Journal of Applied Mathematics, 2014 MEMS/GPS integrated navigation system has been widely used for land-vehicle navigation. This system exhibits large errors because of its nonlinear model and uncertain noise statistic characteristics.
Jianhua Cheng +4 more
doaj +1 more source