Article
Computer Science, Information Systems
Jun Zhao, Renzhou Gui, Xudong Dong, Sunyong Wu
Summary: This study proposes a DOA tracking algorithm based on the GLMB filter, which achieves MAM matching by utilizing the estimated source number from the previous time step. By combining particle filtering and exponentially weighting the likelihood function, it optimizes the posterior distribution, leading to better performance in multi-source DOA tracking.
Article
Computer Science, Artificial Intelligence
Oliver Toero, Tamas Becsi
Summary: State estimation for nonlinear systems is a challenging problem, especially in high dimensions, despite advances in computing power. A novel particle filter approach was introduced in 2007 by Daum and Huang, which utilizes a homotopy-induced particle flow for the Bayesian update step. The exact flow considered in this work is a first-order linear ordinary time-varying inhomogeneous differential equation for the particle motion. An analytic solution is derived for the scalar measurement case, enabling faster computation of the Bayesian update step for particle filters.
INFORMATION FUSION
(2023)
Article
Computer Science, Interdisciplinary Applications
Nicholas Michaud, Perry de Valpine, Daniel Turek, Christopher J. Paciorek, Dao Nguyen
Summary: nimble is an R package that provides flexibility in model specification and allows users to program model-generic algorithms. nimbleSMC is an extension package that contains algorithms for state-space model analysis using SMC techniques.
JOURNAL OF STATISTICAL SOFTWARE
(2021)
Article
Engineering, Mechanical
Neha Aswal, Subhamoy Sen, Laurent Mevel
Summary: Tensegrities are a special type of truss structure where compression members float within a network of tension members. Over time, cables may lose their pre-stress and bars may buckle or corrode, affecting structural stiffness. Tensegrity structures can change their form and stiffness by altering member pre-stress upon loading, potentially masking the effect of damage.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Engineering, Marine
Yuxin Zhao, Shuo Yang, Di Zhou, Xiong Deng, Mengbin Zhu
Summary: This paper introduces an improved particle filter method for data assimilation in geoscientific systems, showing better performance compared to traditional methods, especially under sparse observation conditions where it significantly reduces root mean square error.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2021)
Article
Health Care Sciences & Services
Yusuke Saigusa, Shinto Eguchi, Osamu Komori
Summary: The generalized linear mixed model (GLMM) is a common method for analyzing longitudinal and clustered data in biological sciences. However, issues of model complexity and misspecification can arise. This paper extends the standard GLMM to a nonlinear mixed-effects model based on quasi-linear modeling, providing an estimation algorithm and a conditional AIC for the proposed model. Performance under model misspecification is evaluated in simulation studies, and the proposed model is shown to capture heterogeneity in respiratory illness data.
STATISTICAL METHODS IN MEDICAL RESEARCH
(2022)
Article
Energy & Fuels
Joonchul Kim, Eunsong Kim, Jung-Hwan Park, Kyoung-Tak Kim, Joung-Hu Park, Taesic Kim, Kyoungmin Min
Summary: This study investigated the impact of data partitioning methods on predicting the remaining useful life (RUL) of batteries. Results showed that the method of adding predicted data from a surrogate model to the training set had the highest accuracy, with an average mean absolute error (MAE) of 47 cycles. In contrast, the slide BOX method, which used only certain cycles before the test set as the training set, had the worst MAE value of 60 cycles. Therefore, this data partitioning method can be implemented to predict the RUL of batteries and aid in the development of next-generation cathode materials with improved performance and stability, as well as achieve reliable predictive maintenance.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2023)
Review
Engineering, Multidisciplinary
Chanin Kuptametee, Nattapol Aunsri
Summary: This paper presents the particle filtering method and its application in nonlinear non-Gaussian systems, focusing on the impact of the resampling step on filtering performance. It also classifies and describes recent efficient resampling schemes based on particle weights.
Article
Geosciences, Multidisciplinary
Hannes Helmut Bauser, Daniel Berg, Kurt Roth
Summary: This study investigates the characteristics of divergent and convergent geophysical systems in relation to data assimilation methods, showing that a sufficient divergent component is necessary for proper application of sequential ensemble data assimilation methods. The transfer of methods from divergent to convergent systems is challenging, highlighting the importance of adequately representing model errors and incorporating parameter uncertainties in ensemble data assimilation for convergent systems.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2021)
Article
Automation & Control Systems
Juan-Carlos Santos-Leon, Ramon Orive, Daniel Acosta, Leopoldo Acosta
Summary: This paper revisits the construction and effectiveness of the Cubature Kalman Filter (CKF) and its extensions for higher precision, establishing stable cubature rules within a mathematical framework of numerical integration. By discretizing higher order partial derivatives, stable rules for degrees 5 and 7 are provided and tested for application in filter algorithms through various examples.
Article
Ecology
Seiji Ohshimo, Soyoka Muko, Mari Yoda, Hiroyuki Kurota
Summary: This study evaluated the habitat and abundance of Japanese Spanish mackerel in the Yellow Sea, East China Sea, and Sea of Japan using a generalized additive model and generalized linear model on catch per unit effort (CPUE) data from Japanese purse-seine vessels. The results showed that Japanese Spanish mackerel prefer regions of low temperature at 10 m depth, with a high CPUE area observed in the Yellow and East China seas from 1994 to 1997. The CPUE values increased until 2000, with fluctuations thereafter and stability after 2010. It is the first stock assessment report based on the Japanese large and mid-sized purse seine fishery in the region, suggesting further collaboration with China and Korea for accurate stock assessment and management of the species.
REGIONAL STUDIES IN MARINE SCIENCE
(2021)
Article
Engineering, Electrical & Electronic
Jonathan M. M. Knowles, Hjalti H. H. Sigmarsson, Jay W. W. McDaniel
Summary: In this article, a generalized theory of bandpass filtering attenuators (filtenuators) is proposed, which combines the frequency-selective characteristics of a filter and the loss-programmable characteristics of an attenuator into a single component. A loss-programmable, third-order Chebyshev bandpass filtenuator is designed, fabricated, and measured to verify the theory. The proposed filtenuator offers a tunable, low-cost, size, weight, and power (C-SWaP) solution to increase radio frequency (RF) system dynamic range, and provides a design process for future development of filtenuators.
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES
(2023)
Article
Robotics
Ramazan Havangi
Summary: An improved FastSLAM method based on RSRCKF with partial genetic resampling is proposed in this paper. The method does not require prior knowledge of noise statistics and utilizes genetic operators to maintain particle diversity, resulting in significantly more accurate and robust estimation results compared to other methods. Additionally, the proposed method demonstrates better consistency than existing methods in simulation and experimental data comparisons.
Article
Computer Science, Artificial Intelligence
Lei Wang, Hongrui Cao, Yang Fu
Summary: This paper proposes a hybrid prognosis framework for bearings based on time-varying 3 Sigma criterion, DWELM, and PF. The framework can effectively detect fault occurrence time and accurately estimate the residual useful life of bearings, showing better performance compared to other competing methods.
APPLIED SOFT COMPUTING
(2022)
Article
Automation & Control Systems
S. Kanthalakshmi, M. Raghappriya
Summary: This paper presents a fault detection and diagnosis scheme for stochastic non-linear systems using particle filter. The algorithm utilizes a bank of particle filters running in parallel to monitor system states and detect faults occurrence through log-likelihood ratio-based hypothesis testing, showing effectiveness compared with residual generation methods.
INTERNATIONAL JOURNAL OF CONTROL
(2022)
Article
Multidisciplinary Sciences
Joseph Feingold, Daniel J. Gibson, Brian DePasquale, Ann M. Graybiel
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2015)
Article
Neurosciences
L. F. Abbott, Brian DePasquale, Raoul-Martin Memmesheimer
NATURE NEUROSCIENCE
(2016)
Article
Multidisciplinary Sciences
Brian DePasquale, Christopher J. Cueva, Kanaka Rajan, G. Sean Escola, L. F. Abbott
Article
Multidisciplinary Sciences
Matthew F. Panichello, Brian DePasquale, Jonathan W. Pillow, Timothy J. Buschman
NATURE COMMUNICATIONS
(2019)
Article
Neurosciences
Lucas Pinto, Kanaka Rajan, Brian DePasquale, Stephan Y. Thiberge, David W. Tank, Carlos D. Brody
Article
Biology
Michele N. Insanally, Ioana Carcea, Rachel E. Field, Chris C. Rodgers, Brian DePasquale, Kanaka Rajan, Michael R. DeWeese, Badr F. Albanna, Robert C. Froemke