Results 41 to 50 of about 94,605 (282)
A Probabilistic Perspective on Gaussian Filtering and Smoothing
, 2010 We present a general probabilistic perspective on Gaussian filtering and smoothing. This allows us to show that common approaches to Gaussian filtering/smoothing can be distinguished solely by their methods of computing/approximating the means and ...
Deisenroth, MP, Ohlsson, H
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
Measurement of ship's magnetization parameters based on Kalman filtering method
Zhongguo Jianchuan Yanjiu, 2022 ObjectivesThis study proposes a measurement scheme based on the Kalman filtering method for improving efficiency and lowering complexity in measuring the magnetization parameters of shipboard three-component geomagnetic field measurement systems ...
Hui YAN, Guohua ZHOU
doaj +1 more source
Toward Environmentally Friendly Hydrogel‐Based Flexible Intelligent Sensor Systems
Advanced Intelligent Discovery, EarlyView.This review summarizes environmentally and biologically friendly hydrogel‐based flexible sensor systems focusing on physical, chemical, and physiological sensors. Furthermore, device concepts moving forward for the practical application are discussed about wireless integration, the interface between hydrogel and dry electronics, automatic data analysis
Sudipta Kumar Sarkar, Kuniharu Takei
wiley +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
Robust Kalman Filtering under Model Perturbations
, 2016 We consider a family of divergence-based minimax approaches to perform robust filtering. The mismodeling budget, or tolerance, is specified at each time increment of the model.
Zorzi, Mattia
core +1 more source
Investigation of LSTM Based Prediction for Dynamic Energy Management in Chip Multiprocessors [PDF]
, 2018 In this paper, we investigate the effectiveness of using long short-term memory (LSTM) instead of Kalman filtering to do prediction for the purpose of constructing dynamic energy management (DEM) algorithms in chip multi-processors (CMPs).
Moghaddam, Milad Ghorbani +2 more
core +2 more sources
Advanced Intelligent Discovery, EarlyView.Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +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
Application of Strong Tracking Modified SRCKF Algorithm in Single Observer Passive Tracking [PDF]
Jisuanji gongcheng, 2016 In order to improve the performance of Square Root Cubature Kalman Filtering(STSRCKF) algorithm to track maneuvering target in single observer passive tracking,a Strong Tracking Modified SRCKF(ST-MSRCKF) algorithm is presented.Target state variables and ...
ZHANG Zhuoran,YE Guangqiang,ZHAO Xiaolin
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