LDPC-coded unitary space-time modulation with low-complexity iterative demodulate-decoding scheme by Li-jiao WANG, Lin ZHANG, Ling-ling YANG, Li PENG, Da-wei FU

“…At the receiver, the maximum a posteriori probability (MAP) de-modulating algorithm of the SC-USTM was first designed; for reducing the complexity of MAP demodulator, the dual demodulator was then conceived; for improving the performance, the iterative feedback between the belief propagation (BP) decoder and the MPA demodulator was finally introduced. …”
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High-Precision and Low-Complexity Symbol Synchronization Algorithm Based on Dual-Threshold Amplitude Decision for Real-Time IMDD OFDM-PON by Junjie Peng, You Sun, Haoshuo Chen, Tingting Xu, Zhengxuan Li, Qianwu Zhang, Junjie Zhang

“…Experimental results show that 95% synchronization precision rate can be achieved after 25 km standard single-mode fiber transmission with the received optical power as low as –21 dBm. Compared with the previously proposed one threshold symbol synchronization algorithm, the synchronization performance has been greatly improved, which brings a maximum signal bit rate gain of 35% when the received optical power is lower than –16 dBm. …”
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Maximizing the Total Profit of Combined Systems with a Pumped Storage Hydropower Plant and Renewable Energy Sources Using a Modified Slime Mould Algorithm by Le Chi Kien, Ly Huu Pham, Minh Phuc Duong, Tan Minh Phan

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Approaching maximum resolution in structured illumination microscopy via accurate noise modeling by Ayush Saurabh, Peter T. Brown, J. Shepard Bryan IV, Zachary R. Fox, Rory Kruithoff, Cristopher Thompson, Comert Kural, Douglas P. Shepherd, Steve Pressé

“…Consequently, achieving high contrast near the maximum theoretical resolution in an unsupervised, physically principled manner remains an open problem. …”
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exoALMA. IX. Regularized Maximum Likelihood Imaging of Non-Keplerian Features by Brianna Zawadzki, Ian Czekala, Maria Galloway-Sprietsma, Jaehan Bae, Marcelo Barraza-Alfaro, Myriam Benisty, Gianni Cataldi, Pietro Curone, Stefano Facchini, Daniele Fasano, Mario Flock, Misato Fukagawa, Himanshi Garg, Cassandra Hall, Thomas Hilder, Jane Huang, John D. Ilee, Andrea Isella, Andrés F. Izquierdo, Kazuhiro Kanagawa, Geoffroy Lesur, Cristiano Longarini, Ryan A. Loomis, Ryuta Orihara, Christophe Pinte, Daniel J. Price, Giovanni Rosotti, Jochen Stadler, Richard Teague, Hsi-Wei Yen, Gaylor Wafflard-Fernandez, David J. Wilner, Andrew J. Winter, Lisa Wölfer, Tomohiro C. Yoshida

“…The exoALMA collaboration employed two different imaging procedures to ensure the consistent detection of NKFs: CLEAN, the standard iterative deconvolution algorithm, and regularized maximum likelihood (RML) imaging. …”
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Implementation of a low-cost current perturbation-based improved PO MPPT approach using Arduino board for photovoltaic systems by Abdelkhalek Chellakhi, Said El Beid, Mouncef El Marghichi, El Mahdi Bouabdalli, Ambe Harrison, Hassan Abouobaida

“…However, the fixed perturbation step size used in the traditional PO algorithm can result in poor tracking capability, excessive ripple, and drift, leading to high power loss and low tracking efficiency. …”
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Application of multi-objective neural network algorithm in industrial polymerization reactors for reducing energy cost and maximising productivity by Fakhrony Sholahudin Rohman, Sharifah Rafidah Wan Alwi, Dinie Muhammad, Ashraf Azmi, Zainuddin Abd Manan, Jeng Shiun Lim, Hong An Er, Siti Nor Azreen Ahmad Termizi

“…Due to the significant power required for compression and the high costs of reactant materials, optimizing low-density polyethylene (LDPE) production to provide maximum productivity with a reduction of energy cost is required. …”
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Operational Analysis of Power Generation from a Photovoltaic–Wind Mix and Low-Emission Hydrogen Production by Arkadiusz Małek, Andrzej Marciniak

“…Low-emission hydrogen generation systems require large amounts of energy from renewable energy sources. …”
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Fast OMP algorithm and its FPGA implementation for compressed sensing‐based sparse signal acquisition systems by Shirshendu Roy, Debiprasad P. Acharya, Ajit K. Sahoo

“…Abstract Compressed sensing‐based radio frequency signal acquisition systems call for higher reconstruction speed and low dynamic power. In this study, a novel low power fast orthogonal matching pursuit (LPF‐OMP) algorithm is proposed for faster reconstruction of sparse signals from their compressively sensed samples and the reconstruction circuit consumes very low dynamic power. …”
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Handover Strategy for LEO Satellite Networks Using Bipartite Graph and Hysteresis Margin by Sahar Eydian, Maryam Hosseini, Gunes Karabulut Kurt

“…The proposed approach utilizes the Kuhn-Munkres (KM) algorithm to achieve optimal matching with maximum weight, thereby ensuring efficient load distribution and high-quality communication. …”
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A Novel Maximum Power Point Inference Method for Distributed Marine Photovoltaic Monitoring by Yujie Chen, Jianan Wang, Lele Peng, Jiachen Qiao

“…Subsequently, the Crested Porcupine Optimizer (CPO) algorithm is used to achieve high-precision recognition of the maximum power point in distributed marine photovoltaic monitoring. …”
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Research on Multi-train Cooperative Utilization of Regenerative Braking Energy for Low-speed Maglev Traffic by JIAO Yanjun, LIU Sikai, MA Xiao, LIU Shaoke

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Physics-Informed Deep Neural Network for Low Sidelobe Time-Modulated Antenna Array Synthesis With Harmonic Suppression by Tarek Sallam, Qun Wang, Ahmed M. Attiya

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Chaotic dynamics analysis and digital hardware design of the Izhikevich neuron model by Mehdi Nadiri Andabili, Soheila Nazari, Tohid Moosazadeh

“…The advancement of neuromorphic algorithms can continue to evolve in accordance with the principles of neural computing and the architectures of neural networks that draw inspiration from biological neural systems. …”
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A comparison of the image quality between deep learning reconstruction algorithm and iDose4 using low dose abdominopelvic computed tomography for individuals with normal BMI by Thejas Marike Shivakumar, Nitika C. Panakkal, Shailesh Nayak, Rajagopal Kadavigere, Tanushree R. Kamath, Suresh Sukumar

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16QAM Blind Equalization via Maximum Entropy Density Approximation Technique and Nonlinear Lagrange Multipliers by R. Mauda, M. Pinchas

“…Recently a new blind equalization method was proposed for the 16QAM constellation input inspired by the maximum entropy density approximation technique with improved equalization performance compared to the maximum entropy approach, Godard’s algorithm, and others. …”
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Integrating petrophysical data into efficient iterative cluster analysis for electrofacies identification in clastic reservoirs by Mohammed A. Abbas, Watheq J. Al-Mudhafar, Aqsa Anees, David A. Wood

“…The latent variables include shale volume and water saturation. The EM algorithm efficiently characterizes electrofacies through iterative machine learning to identify the local maximum likelihood estimates (MLE) of the observable and latent variables in the studied dataset. …”
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Chain hybrid feature selection algorithm based on improved Grey Wolf Optimization algorithm. by Xiaotong Bai, Yuefeng Zheng, Yang Lu, Yongtao Shi

“…In this paper, we propose a new hybrid feature selection algorithm, to be named as Tandem Maximum Kendall Minimum Chi-Square and ReliefF Improved Grey Wolf Optimization algorithm (TMKMCRIGWO). …”
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Can Different Cultivars of <i>Panicum maximum</i> Be Identified Using a VIS/NIR Sensor and Machine Learning? by Gelson dos Santos Difante, Gabriela Oliveira de Aquino Monteiro, Juliana Caroline Santos Santana, Néstor Eduardo Villamizar Frontado, Jéssica Gomes Rodrigues, Aryadne Rhoana Dias Chaves, Dthenifer Cordeiro Santana, Izabela Cristina de Oliveira, Luis Carlos Vinhas Ítavo, Fabio Henrique Rojo Baio, Gabriela Souza Oliveira, Carlos Antonio da Silva Junior, Vanessa Zirondi Longhini, Alexandre Menezes Dias, Paulo Eduardo Teodoro, Larissa Pereira Ribeiro Teodoro

“…The objectives of this study were to identify ML models able to differentiate <i>P. maximum</i> cultivars and determine which is the best spectral input for these algorithms and whether reducing the sample size improves the response of the algorithms. …”
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An Over-the-Air Multi-User Convolutional Code for URLLC by Rafael Santos, Daniel Castanheira, Adao Silva, Atilio Gameiro

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