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Biomedical Signal Denoising Via Permutating, Thresholding and Averaging Noise Components Obtained from Hierarchical Multiresolution Analysis-Based Empirical Mode Decomposition
Biomedical signals are usually contaminated with interfering noise, which may result in misdiagnosis of diseases. Additive white Gaussian noise...
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Convolution Hierarchical Deep-Learning Neural Network Tensor Decomposition (C-HiDeNN-TD) for high-resolution topology optimization
High-resolution structural topology optimization is extremely challenging due to a large number of degrees of freedom (DoFs). In this work, a...
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Convolution Hierarchical Deep-learning Neural Networks (C-HiDeNN): finite elements, isogeometric analysis, tensor decomposition, and beyond
This paper presents a general Convolution Hierarchical Deep-learning Neural Networks (C-HiDeNN) computational framework for solving partial...
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Combined task and motion planning system for the service robot using hierarchical action decomposition
A service robot needs integration of symbolic reasoning for high-level task planning and geometric computation for low-level motion planning to...
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Application of hierarchical symbolic fuzzy entropy and sparse Bayesian ELM to bearing fault diagnosis
Bearing fault diagnosis is essential for reducing equipment operating and maintenance costs. We propose a bearing fault diagnosis method that...
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A general integrated procedure for uncertainty-based design optimization of multilevel systems by hierarchical decomposition framework
Several subsystems with hierarchical relationship compose a multilevel system, each of which may have uncertainties in material properties and...
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A hierarchical branch and bound algorithm for Mahjong deficiency
As a testbed for the development of artificial intelligence (AI) techniques, Mahjong has become a hot spot in computer game research due its...
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Hierarchical Gradient-Based Iterative Parameter Estimation Algorithms for a Nonlinear Feedback System Based on the Hierarchical Identification Principle
This paper focuses on iterative parameter estimation methods for a nonlinear closed-loop system (i.e., a nonlinear feedback system) with an...
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Evaluating the effectiveness of functional decomposition in early-stage design: development and application of problem space exploration metrics
This paper aims to explore metrics for evaluating the effectiveness of functional decomposition methods regarding problem space exploration at the...
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Hierarchical Tucker Tensor Regression: A Case Study on Classification
Regression and Classification are two of the important problems in Machine Learning. Despite the differences, there is overlap between these two...
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Multi-theme hierarchical monitoring method for wireless sensor networks
In large-scale industrial and agricultural production environments, many nodes of the Internet of Things (IoT) were deployed. These nodes are of...
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Multi-order attribute network representation learning via constructing hierarchical graphs
Network representation learning (NRL) is widely used for such tasks as link prediction, node classification in network analysis. For NRL, it is a...
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Hierarchical Decomposition of Third-Order Tensor Through Adaptive Branched Inverse Difference Pyramid Based on 3D-WHT
New approach is presented for adaptive decomposition of large-size tensors in the spectrum domain, based on the Three-Dimensional Adaptive Branched...
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Tensor Decomposition
Tensor decompositions provide a powerful platform for dimensionality reduction, which is the fundamental of high-dimensional data analysis. They can...
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Features of the Decomposition of Nonlinear Processes and Systems Within the Framework of the System Approach
The article describes a method for modeling a technological process, which can be represented as a non-linear system. The proposed method allows...
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Hierarchical node method for solving large-scale sparse linear equations in parallel
In this paper, the hierarchical node method (HNM) is proposed for solving large-scale sparse linear equations in the context of elastic mechanics....
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Fault diagnosis of rotating machines based on modified hierarchical fluctuation dispersion entropy and multi-cluster feature selection
The vibration signal of rotating mechanical equipment contains a large amount of information that can be used for the fault diagnosis of rotating...
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Structural Engineering of Hierarchical Magnetic/Carbon Nanocomposites via In Situ Growth for High-Efficient Electromagnetic Wave Absorption
Materials exhibiting high-performance electromagnetic wave absorption have garnered considerable scientific and technological attention, yet...
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Hierarchical Optimal Reactive Power Dispatch for Active Distribution Network with Multi-microgrids
The interconnection of active distribution network and multi-microgrids leads to the increase of variable dimension of optimal reactive power...
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Models and Algorithms for Multiagent Hierarchical Routing with Time Windows
AbstractThe problem of modeling real logistics systems arranged in a hierarchical manner is considered. Clusters of lower level consumers are formed...
