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Modeling of a high gain two stage pHEMT LNA using ANN with Bayesian regularization algorithm
This paper presents novel way to achieve fast and accurate Artificial Neural Network (ANN) modeling of Radio Frequency (RF) front end Low Noise...
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Kernel Regularization Based Volterra Series Identification Method for Time-delayed Nonlinear Systems with Unknown Structure
This paper develops a kernel regularization based Adam algorithm for nonlinear systems with unknown structure and time-delay by using self-organized...
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A Bayesian regularization network approach to thermal distortion control in 3D printing
In this work, a Bayesian Regularization Network based Geometric Deviation Control (BRN-GDC) algorithm is developed to mitigate thermal distortion in...
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Regularization based reweighted estimation algorithms for nonlinear systems in presence of outliers
Outliers usually occur during industrial data collection process and can lead to poor system identification performance. This paper considers the...
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Enhancing framelet GCNs with generalized p-Laplacian regularization
Graph neural networks (GNNs) have achieved remarkable results for various graph learning tasks. However, one of the recent challenges for GNNs is to...
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A robust target tracking algorithm based on spatial regularization and adaptive updating model
The correlation filtering-based target tracking method has impressive tracking performance and computational efficiency. Nevertheless, a few issues...
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SEBR: Scharr Edge-Based Regularization Method for Blind Image Deblurring
The main objective of blind image deblurring is to restore a high-quality sharp image from a blurry input through estimation of unknown blur kernel...
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Frictional node-to-segment contact analysis based on the modified area regularization technique
Node-to-segment (NTS) contact algorithm based on the penalty method remains significant in the industry owing to its computational efficiency and...
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Saturation-value based higher-order regularization for color image restoration
In this article, we introduce saturation-value based higher-order (SV-HO) regularizers and propose several color image restoration models using these...
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Multi-class feature selection via Sparse Softmax with a discriminative regularization
Feature selection plays a critical role in many machine learning applications as it effectively addresses the challenges posed by “the curse of...
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Identifying spatiotemporal information of the point pollutant source indoors based on the adjoint-regularization method
Fast and accurate identification of the pollutant source location and release rate is important for improving indoor air quality. From the...
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Hybrid regularization inspired by total variation and deep denoiser prior for image restoration
Image restoration is a fundamental problem in computer vision, with the goal of restoring high-quality images from degraded low-quality observation...
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Privileged Learning Using Regularization in the Problem of Evaluating the Human Posture
AbstractThe problem of evaluating a person’s posture from video data is solved. Various key points of the human body are analyzed. We study the...
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Uniqueness and Stability of Solving the Inverse Problem of Thermoelasticity. Part 2. Regularization
Based on the analysis of direct variational methods used in the Hilbert space — the regularization method and the iterative regularization method —...
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Reducing the Overfitting in Convolutional Neural Network using Nature-Inspired Algorithm: A Novel Hybrid Approach
Convolutional neural network (CNN) is one of the well-known deep learning algorithms that uses convolutional filters to extract the features in the...
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Robust graph neural networks with Dirichlet regularization and residual connection
Graph Neural Network (GNN) has attracted considerable research interest in various graph data modeling tasks. Most GNNs require efficient and...
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Self-representation with adaptive loss minimization via doubly stochastic graph regularization for robust unsupervised feature selection
Unsupervised feature selection (UFS), which involves selecting representative features from unlabeled high-dimensional data, has attracted much...
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Sine Cosine Algorithm with Tangent Search for Neural Networks Dropout Regularization
Convolutional neural networks belong to the group of deep learning methods, largely influenced by the structure and functioning of the human brain....
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Regularization of the Final Value Problem for the Time-Fractional Diffusion Equation
We consider the backward problem of reconstructing the initial condition of a nonhomogeneous time-fractional diffusion equation from final...
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Adaptive unsupervised feature selection with robust graph regularization
Unsupervised feature selection, aiming at finding a refined representation of the original data by filtering out irrelevant and redundant features,...
