Search engine for discovering works of Art, research articles, and books related to Art and Culture
Javascript must be enabled to continue!
Sage–Husa Algorithm Based on Adaptive Double Forgetting Factors
View through CrossRef
In order to address the issues of insufficient filtering accuracy and filtering divergence that have been observed in the Sage–Husa algorithm when applied to nonlinear system state estimation, an adaptive double forgetting factor-based Sage–Husa algorithm is proposed. This algorithm builds upon the Sage–Husa algorithm with forgetting factors by introducing double forgetting factors and adaptively adjusting them using a windowing method combined with an exponential form. On the basis of ensuring the semi-positive definiteness of the process noise covariance matrix and the positive definiteness of the observation noise covariance matrix, a covariance matching technique is employed to determine whether the measurement noise statistical characteristics need to be re-updated. The results of the simulations demonstrate that the proposed algorithm enhances the accuracy of filtering and exhibits strong effectiveness and feasibility.
Title: Sage–Husa Algorithm Based on Adaptive Double Forgetting Factors
Description:
In order to address the issues of insufficient filtering accuracy and filtering divergence that have been observed in the Sage–Husa algorithm when applied to nonlinear system state estimation, an adaptive double forgetting factor-based Sage–Husa algorithm is proposed.
This algorithm builds upon the Sage–Husa algorithm with forgetting factors by introducing double forgetting factors and adaptively adjusting them using a windowing method combined with an exponential form.
On the basis of ensuring the semi-positive definiteness of the process noise covariance matrix and the positive definiteness of the observation noise covariance matrix, a covariance matching technique is employed to determine whether the measurement noise statistical characteristics need to be re-updated.
The results of the simulations demonstrate that the proposed algorithm enhances the accuracy of filtering and exhibits strong effectiveness and feasibility.
Related Results
Improved 2RC-PNGV Modeling and Adaptive Sage-Husa H Infinity Filtering for Battery Power State Estimation Based on Multi-Parameter Constraints
Improved 2RC-PNGV Modeling and Adaptive Sage-Husa H Infinity Filtering for Battery Power State Estimation Based on Multi-Parameter Constraints
With the transformation of the global energy landscape, lithium-ion batteries have become an important component in the field of new energy storage. Accurate assessment of battery ...
Association of Accelerated Long-term Forgetting and Senescence-related Blood-borne Factors in Asymptomatic Individuals From Families With Autosomal Dominant Alzheimer’s Disease
Association of Accelerated Long-term Forgetting and Senescence-related Blood-borne Factors in Asymptomatic Individuals From Families With Autosomal Dominant Alzheimer’s Disease
Abstract
Background: Accelerated long-term forgetting has been identified in preclinical Alzheimer’s disease (AD), and is attributed to a selective impairment of memory con...
Some Functions of Collective Forgetting
Some Functions of Collective Forgetting
Coerced forgetting — forgetting as repressive erasure — has been a hallmark of many of the totalitarian regimes of the 20th century. However, the act of forgetting is not always ne...
Tableau-based Forgetting in 𝒜ℒ𝒞 Ontologies
Tableau-based Forgetting in 𝒜ℒ𝒞 Ontologies
In this paper, we propose two new approaches to forgetting for 𝒜ℒ𝒞 based on the well-known tableau algorithm. The first approach computes the result of f...
DLS-Forgetter: An Implementation of the DLS Forgetting Calculus for First-Order Logic
DLS-Forgetter: An Implementation of the DLS Forgetting Calculus for First-Order Logic
DLS-Forgetter is a reasoning tool that aims to compute restricted views of a knowledge base of first-order logic formulae via semantic forgetting. Semantic forgetting achieves this...
An Adaptive Extended Kalman Filter Observer-For Permanent Magnet Synchronous Motor Position Sensorless Control Systems
An Adaptive Extended Kalman Filter Observer-For Permanent Magnet Synchronous Motor Position Sensorless Control Systems
Abstract
In this paper, an improved Sage-Husa adaptive extended Kalman filter observer is proposed to accurately estimate rotor speed and electrical angle in Position Senso...
Sleep prevents catastrophic forgetting in spiking neural networks by forming joint synaptic weight representations
Sleep prevents catastrophic forgetting in spiking neural networks by forming joint synaptic weight representations
AbstractArtificial neural networks overwrite previously learned tasks when trained sequentially, a phenomenon known as catastrophic forgetting. In contrast, the brain learns contin...
Direct remembering, mediated remembering, and atypical forgetting functions
Direct remembering, mediated remembering, and atypical forgetting functions
Atypical forgetting functions have been demonstrated in several recent studies of delayed matching to sample, in which experimental conditions are altered partway through the reten...