A Joint Sparse Space-Time Adaptive Processing Method by Jinfeng Hu, Yuyan Xia, Huiyong Li, Jing Liang, Tao Lin

“…At present, most of the sparse space-time adaptive processing(STAP) methods focus on exploiting the clutter sparsity. …”
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Improved Variational Bayes for Space-Time Adaptive Processing by Kun Li, Jinyang Luo, Peng Li, Guisheng Liao, Zhixiang Huang, Lixia Yang

“…To tackle the challenge of enhancing moving target detection performance in environments characterized by small sample sizes and non-uniformity, methods rooted in sparse signal reconstruction have been incorporated into Space-Time Adaptive Processing (STAP) algorithms. …”
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Localisation and classification of mixed far‐field and near‐field sources with sparse reconstruction by Meidong Kuang, Yuexian Wang, Ling Wang, Jian Xie, Chuang Han

“…However, the existing selection strategy of the tuning factor is not adaptive to different observation scenarios. So a closed‐form expression of the tuning factor based on the FOC estimation error is presented. …”
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Improving Presentation Attack Detection Classification Accuracy: Novel Approaches Incorporating Facial Expressions, Backdrops, and Data Augmentation by Tayyaba Riaz, Adeel Anjum, Madiha Haider Syed, Semeen Rehman

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Acoustic field visualization and source localization via physics-informed learning of sparse data with adaptive sampling by Jian Chen, Dan Xu, Weijian Fang, Shiwei Wu, Haiteng Wu

“…In this study, we propose an approach for acoustic field visualization based on physics-informed neural networks (PINNs) by using a small amount of data, subsequently realizing accurate acoustic source localization. First, we present a PINN model integrated with an acoustic Helmholtz equation and adaptive sampling, the performance of which is testified via numerical simulations. …”
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Singular Value Decomposition-Based Adaptive Sampling Approximate Message Passing Net for Sparse-View CT Reconstruction by Zhenhua Wu, Jiafei Xu, Lixia Yang

“…In this paper, to address these challenges, we present a singular value decomposition-based adaptive sampling approximate message passing network (ASAMP-Net) sparse-view CT imaging method. …”
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A Sparse Variable Step-Size Least-Mean-Square Algorithm for Impulsive Noise in a Code-Division Multiple Access System by Mohammad Salman, Ahmed A. F. Youssef, Fahmi Elsayed, Mostafa Rashdan

“…In this work, we propose a sparse variable step-size LMS approach in a code-division multiple access (CDMA) system. …”
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SE-TFF: Adaptive Tourism-Flow Forecasting Under Sparse and Heterogeneous Data via Multi-Scale SE-Net by Jinyuan Zhang, Tao Cui, Peng He

“…This paper presents SE-TFF, a multi-scale tourism-flow forecasting framework that couples a Squeeze-and-Excitation (SE) network with reinforcement-driven optimization to adaptively re-weight environmental, economic, and social features. …”
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Adaptive Filtering for Channel Estimation in RIS-Assisted mmWave Systems by Shuying Shao, Tiejun Lv, Pingmu Huang

“…Extensive simulations validate our findings, with results illustrating the performance of the proposed algorithms under different parameters, demonstrating significant improvements in channel estimation accuracy and convergence speed over established methods, including NLMS, sparse exponential forgetting window least mean square (SEFWLMS), and sparse hybrid adaptive filtering algorithms (SHAFA).…”
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AWGE-ESPCA: An edge sparse PCA model based on adaptive noise elimination regularization and weighted gene network for Hermetia illucens genomic data analysis. by Rui Miao, Hao-Yang Yu, Bing-Jie Zhong, Hong-Xia Sun, Qiang Xia

“…Subsequently, we propose AWGE-ESPCA: an edge Sparse PCA model based on adaptive noise elimination regularization and weighted gene network. …”
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Sparse Array Mutual Coupling Reduction by C. Larmour, N. Buchanan, V. Fusco, M. Ali Babar Abbasi

“…This paper provides a concise overview of recent developments in sparse antenna arrays, with a specific focus on techniques for reducing mutual coupling. …”
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Enhanced Adaptive Wiener Filtering for Frequency-Varying Noise with Convolutional Neural Network-Based Feature Extraction by Chun-Lin Liao, Jian-Jiun Ding, De-Yan Lu

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Sparse Indoor Camera Positioning with Fiducial Markers by Pablo García-Ruiz, Francisco J. Romero-Ramirez, Rafael Muñoz-Salinas, Manuel J. Marín-Jiménez, Rafael Medina-Carnicer

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Evolutionary sparse learning reveals the shared genetic basis of convergent traits by John B. Allard, Sudip Sharma, Ravi Patel, Maxwell Sanderford, Koichiro Tamura, Slobodan Vucetic, Glenn S. Gerhard, Sudhir Kumar

“…Here, we present an approach to build genetic models that underlie the independent origins of convergent traits using evolutionary sparse learning with paired species contrast (ESL-PSC). …”
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Evaluating Sparse Feature Selection Methods: A Theoretical and Empirical Perspective by Monica Fira, Liviu Goras, Hariton-Nicolae Costin

“…The mathematical foundations of feature selection methods inspired by compressed detection are presented, highlighting how the principles of sparse signal recovery can be applied to identify the most relevant features. …”
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Finite Differences on Sparse Grids for Continuous-Time Heterogeneous Agent Models by Jochen Garcke, Steffen Ruttscheidt

“…We present a finite difference method working on sparse grids to solve higher dimensional heterogeneous agent models. …”
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Sparse coding-based multiframe superresolution for efficient synchrotron radiation microspectroscopy by Yasuhiko Igarashi, Naoka Nagamura, Masahiro Sekine, Hirokazu Fukidome, Hideitsu Hino, Masato Okada

“…Abstract In nanostructure extraction, advanced techniques like synchrotron radiation and electron microscopy are often hindered by radiation damage and charging artifacts from long exposure times. This study presents a multiframe superresolution method using sparse coding to enhance synchrotron radiation microspectroscopy images. …”
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Faber-Schauder Wavelet Sparse Grid Approach for Option Pricing with Transactions Cost by Shu-Li Mei

“…The space jump that appeared in the transformation model is suitable to be solved by the sparse grid approach. An adaptive sparse approximation solution of the nonlinear second-order PDEs was constructed using Faber-Schauder wavelet function and the corresponding multiscale analysis theory. …”
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Traffic Sign Detection via Improved Sparse R-CNN for Autonomous Vehicles by Tianjiao Liang, Hong Bao, Weiguo Pan, Feng Pan

“…In order to obtain more diverse data, the augmentation method used is specifically designed for complex traffic scenarios, and we also present a traffic sign dataset in this study. For on-road autonomous vehicles, we designed two modules, self-adaption augmentation (SAA) and detection time augmentation (DTA), to improve the robustness of the detection algorithm. …”
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MIMO High Frequency Surface Wave Radar Using Sparse Frequency FMCW Signals by Mengguan Pan, Baixiao Chen

“…Therefore, we introduce the iterative adaptive approach (IAA) in the range-azimuth imaging. …”
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