Results 1 to 10 of about 152,938 (180)
Kernel recursive least square tracker and long-short term memory ensemble based battery health prognostic model [PDF]
iScience, 2021 Summary: A data-driven approach is developed to predict the future capacity of lithium-ion batteries (LIBs) in this work. The empirical mode decomposition (EMD), kernel recursive least square tracker (KRLST), and long short-term memory (LSTM) are used to
Muhammad Umair Ali +6 more
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Efficient FPGA Implementation of Recursive Least Square Adaptive Filter Using Non- Restoring Division Algorithm [PDF]
International Journal of Electronics and Telecommunications, 2023 In this paper, Recursive Least Square (RLS) and Affine Projection (AP) adaptive filters are designed using Xilinx System Generator and implemented on the Spartan6 xc6slx16- 2csg324 FPGA platform.
Harith H. Thannoon, Ivan A. Hashim
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Identifikasi Motor DC dengan Metode Recursive Least Square
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems), 2021 Motor DC Minertia tipe UGTMEM-03STC25 merupakan salah satu alat di Laboratorium Sistem Kontrol Universitas Brawijaya Malang. Dengan menggunakan metode RLS motor DC Minertia tipe UGTMEM-03STC25 diperoleh model terbaik adalah orde 4 dengan parameter a1 ...
Muhammad Aziz Muslim +2 more
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Minibatch Recursive Least Squares Q‐Learning
Computational Intelligence and Neuroscience, 2021 The deep Q‐network (DQN) is one of the most successful reinforcement learning algorithms, but it has some drawbacks such as slow convergence and instability. In contrast, the traditional reinforcement learning algorithms with linear function approximation usually have faster convergence and better stability, although they easily suffer from the curse ...
Chunyuan Zhang, Qi Song, Zeng Meng
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Mixed-Precision Kernel Recursive Least Squares [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2022 Kernel recursive least squares (KRLS) is a widely used online machine learning algorithm for time series predictions. In this article, we present the mixed-precision KRLS, producing equivalent prediction accuracy to double-precision KRLS with a higher training throughput and a lower memory footprint.
JunKyu Lee +2 more
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FxRLS Algorithms Based Active Control of Impulsive Noise With Online Secondary Path Modeling
IEEE Access, 2021 Active noise control algorithms undergo stability problems in the presence of impulsive noise. This paper investigates such algorithms with online secondary path modeling for impulsive noise and varying acoustic paths.
Fareeha Jabeen +5 more
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Zero Attracting Recursive Least Squares Algorithms [PDF]
IEEE Transactions on Vehicular Technology, 2016 The l1-norm sparsity constraint is a widely used\ud technique for constructing sparse models. In this contribution, two zero-attracting recursive least squares algorithms, referred to as ZA-RLS-I and ZA-RLS-II, are derived by employing the l1-norm of parameter vector constraint to facilitate the model sparsity.
Hong, Xia, Gao, Junbin, Chen, Sheng
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Noise Reduction in RTL-SDR using Least Mean Square and Recursive Least Square
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2020 Noise reduction is an important process in a communication system, one of which is radio communication. In the process of broadcasting radio Frequency Modulation (FM) often encountered noise so that listeners find it difficult to understand the ...
Aviv Yuniar Rahman +2 more
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Lithium battery parameter identification and SOC estimation based on dual-polarized model [PDF]
E3S Web of Conferences, 2021 An equivalent circuit model of dual polarization (DP) of lithium battery was established according to the application characteristics of lithium battery under the standby condition of 5G base station.
Xia Hui +3 more
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Energies, 2022 This paper deals with a method of quantifying the harmonic contribution of each harmonic source to system voltage distortion. Assessing the harmonic contribution of individual harmonic sources is essential for mitigating and managing system harmonic ...
Jong-Il Park, Chang-Hyun Park
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