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Journal articles on the topic 'RLS Algorithm'

Author: Grafiati

Published: 4 June 2021

Last updated: 19 June 2025

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1

Zorkun, Aral Ertug, Miguel A. Salas-Natera, and Ramón Martínez Rodríguez-Osorio. "An Improved Hybrid Beamforming Algorithm for Fast Target Tracking in Satellite and V2X Communication." Remote Sensing 16, no. 1 (2023): 13. http://dx.doi.org/10.3390/rs16010013.

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Autonomous remote sensing systems establish communication links between nodes. Ensuring coverage and seamless communication in highly dense environments is not a trivial task as localization, separation, and tracking of targets, as well as interference suppression, are challenging. Therefore, smart antenna systems fulfill these requirements by employing beamforming algorithms and are considered a key technology for autonomous remote sensing applications. Among many beamforming algorithms, the recursive least square (RLS) algorithm has proven superior convergence and convergence rate performanc

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Prongnuch, Sethakarn, Suchada Sitjongsataporn, and Theerayod Wiangtong. "Diffusion recursive least squares algorithm based on triangular decomposition." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 5 (2023): 5101. http://dx.doi.org/10.11591/ijece.v13i5.pp5101-5108.

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<span lang="EN-US">In this paper, diffusion strategies used by QR-decomposition based on recursive least squares algorithm (DQR-RLS) and the sign version of DQR-RLS algorithm (DQR-sRLS) are introduced for distributed networks. In terms of the QR-decomposition method and Cholesky factorization, a modified Kalman vector is given adaptively with the help of unitary rotation that can decrease the complexity from inverse autocorrelation matrix to vector. According to the diffusion strategies, combine-then-adapt (CTA) and adapt-then-combine (ATC) based on DQR-RLS and DQR-sRLS algorithms are pr

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Khan, Noor M., and Hasan Raza. "Processing-Efficient Distributed Adaptive RLS Filtering for Computationally Constrained Platforms." Wireless Communications and Mobile Computing 2017 (2017): 1–7. http://dx.doi.org/10.1155/2017/1248796.

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In this paper, a novel processing-efficient architecture of a group of inexpensive and computationally incapable small platforms is proposed for a parallely distributed adaptive signal processing (PDASP) operation. The proposed architecture runs computationally expensive procedures like complex adaptive recursive least square (RLS) algorithm cooperatively. The proposed PDASP architecture operates properly even if perfect time alignment among the participating platforms is not available. An RLS algorithm with the application of MIMO channel estimation is deployed on the proposed architecture. C

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4

Xu, X., H. He, and D. Hu. "Efficient Reinforcement Learning Using Recursive Least-Squares Methods." Journal of Artificial Intelligence Research 16 (April 1, 2002): 259–92. http://dx.doi.org/10.1613/jair.946.

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The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is mainly due to its fast convergence speed, which is considered to be optimal in practice. In this paper, RLS methods are used to solve reinforcement learning problems, where two new reinforcement learning algorithms using linear value function approximators are proposed and analyzed. The two algorithms are called RLS-TD(lambda) and Fast-AHC (Fast Adaptive Heuristic Critic), respectively. RLS-TD(lambda) can be viewed as the

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Kostromitsky, S. M., I. N. Davydzenko, and A. A. Dyatko. "Equivalent forms of writing of processing algorithms of adaptive antenna array." Proceedings of the National Academy of Sciences of Belarus, Physical-Technical Series 67, no. 2 (2022): 230–38. http://dx.doi.org/10.29235/1561-8358-2022-67-2-230-238.

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The article is devoted to obtaining equivalent forms of writing of processing algorithms for the operation of adaptive antenna arrays, considering algorithms as varieties of some generalized LMS algorithm. This will facilitate a comparative analysis of the algorithms’ characteristics. The following algorithms of operation are considered: LMS, NLMS, LMS-Newton, SMI, RLS. The article contains the initial operation algorithms of adaptive antenna arrays, conclusions of equivalent processing algorithms and an equivalent block diagram of the generalized LMS algorithm. Equivalent forms of writing the

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Skidmore, I. D., and I. K. Proudler. "The KaGE RLS algorithm." IEEE Transactions on Signal Processing 51, no. 12 (2003): 3094–104. http://dx.doi.org/10.1109/tsp.2003.818997.

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7

Hatun, Metin. "Identification of Wiener Systems with Recursive Gauss-Seidel Algorithm." Elektronika ir Elektrotechnika 29, no. 5 (2023): 4–10. http://dx.doi.org/10.5755/j02.eie.35119.

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The Recursive Gauss-Seidel (RGS) algorithm is presented that is implemented in a one-step Gauss-Seidel iteration for the identification of Wiener output error systems. The RGS algorithm has lower processing intensity than the popular Recursive Least Squares (RLS) algorithm due to its implementation using one-step Gauss-Seidel iteration in a sampling interval. The noise-free output samples in the data vector used for implementation of the RGS algorithm are estimated using an auxiliary model. Also, a stochastic convergence analysis is presented, and it is shown that the presented auxiliary model

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8

Jaros, Rene, Radek Martinek, Radana Kahankova, et al. "Optimization of RLS Algorithm for Hybrid Method ICA-RLS." IFAC-PapersOnLine 52, no. 27 (2019): 530–35. http://dx.doi.org/10.1016/j.ifacol.2019.12.718.

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9

Radhi Shabib Kaned. "Investigation of Phase Noise on the Performance of LMS-RLS Adaptive Equalizer." Diyala Journal of Engineering Sciences 6, no. 1 (2013): 27–35. http://dx.doi.org/10.24237/djes.2013.06103.

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This paper investigates the effect of phase noise on equalization of communication channels using least mean square (LMS) and recursive least square (RLS) adaptive algorithms. The aim of the investigation is to mitigate inter-symbol interference (ISI) caused by the channel and to impose the bit error rate (BER) in the received signals. The equalizerusestwobasicadaptivealgorithms: LMS algorithmand RLS algorithm. Without LMS-RLS equalizer,theBER ismorethan when the system modelincludesLMS-RLS equalizer as indicated in table (1) and table (2). Equalizer algorithm is analyzed using MATLAB v.9 Comm

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10

Chen, Yuan Yuan, Run Jie Liu, Jin Yuan Shen, and Dan Dan He. "The Use of Adaptive Algorithms on Smart Antenna Device." Advanced Materials Research 548 (July 2012): 730–34. http://dx.doi.org/10.4028/www.scientific.net/amr.548.730.

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Adaptive beamforming is one of the core technology of the smart antenna system. Two different adaptive algorithms which adopt the minimum mean square algorithm (LMS) and recursive least squares algorithm (RLS) are employed to realize the beamforming in smart antenna system. The smart antenna system based on LMS and RLS is simulated and realized by the MATLAB software in which a uniform linear adaptive antenna array is used. The results show that the smart antenna systems based on RLS and LMS algorithms can significantly reduce the bit error rate especially with the low SNR.

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11

Shen, Yifan, Jianyong Zhang, Shuchao Mi, Guofang Fan, and Muguang Wang. "Efficient Frequency-Domain Block Equalization for Mode-Division Multiplexing Systems." Photonics 12, no. 2 (2025): 161. https://doi.org/10.3390/photonics12020161.

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In this paper, an adaptive frequency-domain block equalizer (FDBE) implementing the adaptive moment estimation (Adam) algorithm is proposed for mode-division multiplexing (MDM) optical fiber communication systems. By packing all frequency components into frequency-dependent blocks of a specified size B, we define an adaptive equalization matrix to simultaneously compensate for multiple frequency components at each block, which is computed iteratively using the Adam, recursive least squares (RLS) and least mean squares (LMS) algorithms. Simulations show that the proposed FDBE using the Adam alg

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12

Hatun, Metin. "ECG Noise Cancellation with Recursive Gauss-Seidel Algorithm." Karadeniz Fen Bilimleri Dergisi 14, no. 4 (2024): 2115–27. https://doi.org/10.31466/kfbd.1524020.

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Electrocardiogram (ECG) signals provide information about heart functions and some cardiac diseases. However, various interferences distort the ECG waveforms during its measurement and transmission can cause inaccurate analysis and diagnosis. So, this unwanted disturbance signals must be eliminated and an acceptable ECG signal must be extracted the noisy ECG recordings. Researchers developed several methods to overcome the undesired noises and interferences contaminated to the ECG recordings. The adaptive filtering techniques have attracted the attention of scientists due to their adaptation m

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BENESTY, Jacob, Constantin PALEOLOGU, and Silviu CIOCHINA. "Regularization of the RLS Algorithm." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E94-A, no. 8 (2011): 1628–29. http://dx.doi.org/10.1587/transfun.e94.a.1628.

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Babadi, Behtash, Nicholas Kalouptsidis, and Vahid Tarokh. "SPARLS: The Sparse RLS Algorithm." IEEE Transactions on Signal Processing 58, no. 8 (2010): 4013–25. http://dx.doi.org/10.1109/tsp.2010.2048103.

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15

Tang, Jun, Xiqin Wang, and Yingning Peng. "Sub-array RLS adaptive algorithm." Electronics Letters 35, no. 13 (1999): 1061. http://dx.doi.org/10.1049/el:19990737.

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Eksioglu, Ender M., and A. Korhan Tanc. "RLS Algorithm With Convex Regularization." IEEE Signal Processing Letters 18, no. 8 (2011): 470–73. http://dx.doi.org/10.1109/lsp.2011.2159373.

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17

Song, Wenxian, Guofu Wang, and Jincai Ye. "A Novel Digital Predistortion Identification Algorithm Based on Variable Forgetting Factor Recursive Least Square Method." International Journal of RF and Microwave Computer-Aided Engineering 2023 (May 20, 2023): 1–10. http://dx.doi.org/10.1155/2023/6377941.

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The transmitting signal of wireless communication system is impaired by the nonlinearity of RF power amplifier (PA) which leads to signal distortion and spectrum spillover, by which the signal transmission quality is affected. Digital predistortion (DPD) is an efficient and economical way to correct the nonlinear effects of power amplifiers. The recursive least square (RLS) recognition algorithm is commonly used to extract the correction coefficients of the DPD model, and the accuracy of the extraction directly affects the system performance. In this paper, a new variable forgetting factor ide

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Fîciu, Ionuț-Dorinel, Cristian-Lucian Stanciu, Constantin Paleologu, and Jacob Benesty. "Low-Complexity Data-Reuse RLS Algorithm for Stereophonic Acoustic Echo Cancellation." Applied Sciences 13, no. 4 (2023): 2227. http://dx.doi.org/10.3390/app13042227.

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Stereophonic audio devices employ two loudspeakers and two microphones in order to create a bidirectional sound effect. In this context, the stereophonic acoustic echo cancellation (SAEC) setup requires the estimation of four echo paths, each one corresponding to a loudspeaker-to-microphone pair. The widely linear (WL) model was proposed in recent literature in order to simplify the handling of the SAEC mathematical model. Moreover, low complexity recursive least- squares (RLS) adaptive algorithms were developed within the WL framework and successfully tested for SAEC scenarios. This paper pro

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19

Mohammad, Shukri Salman, Eleyan Alaa, and Al-SheikhBahaa Al-Sheikh Bahaa. "Discrete wavelet transform recursive inverse algorithm using second-order estimation of the autocorrelation matrix." TELKOMNIKA Telecommunication, Computing, Electronics and Control 18, no. 6 (2020): 3073~3079. https://doi.org/10.12928/TELKOMNIKA.v18i6.16191.

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The recursive least squares (RLS) algorithm was introduced as an alternative to least mean square (LMS) algorithm with enhanced performance. Computational complexity and instability in updating the autocolleltion matrix are some of the drawbacks of the RLS algorithm that were among the reasons for the introduction of the second-order recursive inverse (RI) adaptive algorithm. The 2nd order RI adaptive algorithm suffered from low convergence rate in certain scenarios that required a relatively small initial step-size. In this paper, we propose a new second-order RI algorithm that projects the i

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20

Lim, Jun-Seok, and Yong-Guk Pyeon. "Kernel RLS Algorithm Using Variable Forgetting Factor." Journal of Korean Institute of Communications and Information Sciences 40, no. 9 (2015): 1793–801. http://dx.doi.org/10.7840/kics.2015.40.9.1793.

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Sung, Chi Wan, and Shiu Yin Yuen. "Analysis of (1+1) Evolutionary Algorithm and Randomized Local Search with Memory." Evolutionary Computation 19, no. 2 (2011): 287–323. http://dx.doi.org/10.1162/evco_a_00029.

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This paper considers the scenario of the (1+1) evolutionary algorithm (EA) and randomized local search (RLS) with memory. Previously explored solutions are stored in memory until an improvement in fitness is obtained; then the stored information is discarded. This results in two new algorithms: (1+1) EA-m (with a raw list and hash table option) and RLS-m+ (and RLS-m if the function is a priori known to be unimodal). These two algorithms can be regarded as very simple forms of tabu search. Rigorous theoretical analysis of the expected time to find the globally optimal solutions for these algori

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22

Guan, Zixi, Raja Varma Pamba, Bhuvaneswari Balachander, Deepak Kumar Khare, Nabamita Deb, and Rajasekhar Boddu. "Retrospection of Nonlinear Adaptive Algorithm-Based Intelligent Plane Image Interaction System." Computational Intelligence and Neuroscience 2022 (March 9, 2022): 1–6. http://dx.doi.org/10.1155/2022/3502830.

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This paper introduces the application and classification of an adaptive filtering algorithm in the image enhancement algorithm. And the filtering noise reduction impact is compared using MATLAB software for programming, image processing, LMS algorithm, RLS algorithm, histogram equalisation algorithm, and Wiener filtering method filtering noise reduction effect. To optimize the intelligent graphic image interaction system, the proposed nonlinear adaptive algorithm of intelligent graphic image interaction system research is based on the digital filter and adaptive filtering algorithm for simulat

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23

Chiheb, Amira, and Hassina Khelladi. "Performance Comparison of LMS and RLS Algorithms for Ambient Noise Attenuation." International Journal of Electrical and Computer Engineering Research 4, no. 1 (2024): 14–19. http://dx.doi.org/10.53375/ijecer.2024.383.

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The aim of this study is to implement two different types of adaptive algorithms for the noise cancellation. The study explores the well-known least mean squares (LMS) adaptive algorithm, which is based on stochastic gradient descent approach, and its performances in terms of noise attenuation level and swiftness in active noise control (ANC). Another algorithm is considered in this investigation based upon the use of the least squares estimation (LSE), commonly named, the recursive least squares algorithm (RLS), and will be compared to the LMS. In order to evaluate the potential of each one,

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24

Christev, Atanas, and Sergey Slobodyan. "LEARNABILITY OF E–STABLE EQUILIBRIA." Macroeconomic Dynamics 18, no. 5 (2013): 959–84. http://dx.doi.org/10.1017/s1365100512000703.

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If private sector agents update their beliefs with a learning algorithm other than recursive least squares, expectational stability or learnability of rational expectations equilibria (REE) is not guaranteed. Monetary policy under commitment, with a determinate and E-stable REE, may not imply robust learning stability of such equilibria if the RLS speed of convergence is slow. In this paper, we propose a refinement of E-stability conditions that allows us to select equilibria more robust to specification of the learning algorithm within the RLS/SG/GSG class. E-stable equilibria characterized b

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Bao, Longsheng, Tianyang Tao, and Ling Yu. "Error Handling Method for Improving BDS Monitoring Accuracy of Bridge Deformation." Advances in Civil Engineering 2022 (March 8, 2022): 1–18. http://dx.doi.org/10.1155/2022/3544885.

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The existing high-tech bridge deformation monitoring technologies mostly use the GPS system. To eliminate the dependence on this system, China has independently developed and built the Beidou satellite navigation system. In this study, an improved algorithm for differently modulated signals is proposed to increase the accuracy of satellite monitoring and minimise the intercode interference into the output signals of the Beidou bridge deformation monitoring system. It includes a modified recurrent least square constant modulus algorithm (RLS-CMA) developed using MATLAB software. The numbers of

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Tajdari, Teimour. "Adaptive method to predict and track unknown system behaviors using RLS and LMS algorithms." Facta universitatis - series: Electronics and Energetics 34, no. 1 (2021): 133–40. http://dx.doi.org/10.2298/fuee2101133t.

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This study investigates the ability of recursive least squares (RLS) and least mean square (LMS) adaptive filtering algorithms to predict and quickly track unknown systems. Tracking unknown system behavior is important if there are other parallel systems that must follow exactly the same behavior at the same time. The adaptive algorithm can correct the filter coefficients according to changes in unknown system parameters to minimize errors between the filter output and the system output for the same input signal. The RLS and LMS algorithms were designed and then examined separately, giving the

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27

Liu, J., and Y. Zakharov. "Low complexity dynamically regularised RLS algorithm." Electronics Letters 44, no. 14 (2008): 886. http://dx.doi.org/10.1049/el:20081096.

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Cioffi, J. M. "An unwindowed RLS adaptive lattice algorithm." IEEE Transactions on Acoustics, Speech, and Signal Processing 36, no. 3 (1988): 365–71. http://dx.doi.org/10.1109/29.1533.

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Cioffi, J. M. "The fast adaptive ROTOR's RLS algorithm." IEEE Transactions on Acoustics, Speech, and Signal Processing 38, no. 4 (1990): 631–53. http://dx.doi.org/10.1109/29.52704.

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30

Naji, Hassan Saadallah, and Husham Idan Hussein. "Application of computational methods for harmonic state estimation of power system networks." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 1 (2021): 1. http://dx.doi.org/10.11591/ijeecs.v22.i1.pp1-9.

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<span>In this study, a novel technique is used to estimate the power system harmonic state, as one of the biggest risks in a power system network. Nonlinear loads are widely used, which inject harmonics into a system. Such injected harmonics make networks unstable and increase power loss. The main objective of this work is to develop a new harmonic state estimator system to increase power system accuracy, stability and the wall operation state. Three computational methods are used in this study, that is, the i) proposed particle swarm optimisation-recursive least squares (PSO-RLS) algori

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Naji, Hassan Saadallah, and Husham Idan Hussein. "Application of computational methods for harmonic state estimation of power system networks." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 1 (2021): 1–9. https://doi.org/10.11591/ijeecs.v22.i1.pp1-9.

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In this study, a novel technique is used to estimate the power system harmonic state, as one of the biggest risks in a power system network. Nonlinear loads are widely used, which inject harmonics into a system. Such injected harmonics make networks unstable and increase power loss. The main objective of this work is to develop a new harmonic state estimator system to increase power system accuracy, stability and the wall operation state. Three computational methods are used in this study, that is, the i) proposed particle swarm optimisation-recursive least squares (PSO-RLS) algorithm, which i

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Elisei-Iliescu, Camelia, Laura-Maria Dogariu, Constantin Paleologu, Jacob Benesty, Andrei-Alexandru Enescu, and Silviu Ciochină. "A Recursive Least-Squares Algorithm for the Identification of Trilinear Forms." Algorithms 13, no. 6 (2020): 135. http://dx.doi.org/10.3390/a13060135.

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High-dimensional system identification problems can be efficiently addressed based on tensor decompositions and modelling. In this paper, we design a recursive least-squares (RLS) algorithm tailored for the identification of trilinear forms, namely RLS-TF. In our framework, the trilinear form is related to the decomposition of a third-order tensor (of rank one). The proposed RLS-TF algorithm acts on the individual components of the global impulse response, thus being efficient in terms of both performance and complexity. Simulation results indicate that the proposed solution outperforms the co

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Cheng, Hui. "The Fuzzy CMAC Based on RLS Algorithm." Applied Mechanics and Materials 432 (September 2013): 478–82. http://dx.doi.org/10.4028/www.scientific.net/amm.432.478.

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In this paper, the structure of the fuzzy crebellar model articulation controller (FCMAC) neural network was discussed. The FCMAC can improve the accuracy of the CMAC. It also has excellent generalization ability and fault-tolerance ability. The recursive least squares (RLS) algorithm was introduced into the FCMAC. The FCMAC based on RLS algorithm has potential application prospect in the research of modeling and emulation on the complex systems.

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Zhang, Xu Dong, Ji Fu Guan, and Liang Gu. "Realization and Comparison of System Identification Based on Different Least Squares Methods." Applied Mechanics and Materials 226-228 (November 2012): 2167–70. http://dx.doi.org/10.4028/www.scientific.net/amm.226-228.2167.

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System identification, which includes parameter identification and non-parameter identification, is to estimate its mathematical model based on the input and output observation in system. This paper discusses the system identification theory and establishes a transfer function of 1/4 vehicle’s second-order vibration system model. Through the discrete transfer function, the system’s difference equation can be obtained to identify the system in two ways, RLS (recursive least squares) and RELS (extended recursive least squares). Finally, the paper makes a comparative analysis about RLS and RELS i

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Fîciu, Ionuț-Dorinel, Cristian-Lucian Stanciu, Cristian Anghel, and Camelia Elisei-Iliescu. "Low-Complexity Recursive Least-Squares Adaptive Algorithm Based on Tensorial Forms." Applied Sciences 11, no. 18 (2021): 8656. http://dx.doi.org/10.3390/app11188656.

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Modern solutions for system identification problems employ multilinear forms, which are based on multiple-order tensor decomposition (of rank one). Recently, such a solution was introduced based on the recursive least-squares (RLS) algorithm. Despite their potential for adaptive systems, the classical RLS methods require a prohibitive amount of arithmetic resources and are sometimes prone to numerical stability issues. This paper proposes a new algorithm for multiple-input/single-output (MISO) system identification based on the combination between the exponentially weighted RLS algorithm and t

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Zha, Fusheng, Wentao Sheng, Wei Guo, Shiyin Qiu, Jing Deng, and Xin Wang. "Dynamic Parameter Identification of a Lower Extremity Exoskeleton Using RLS-PSO." Applied Sciences 9, no. 2 (2019): 324. http://dx.doi.org/10.3390/app9020324.

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The lower extremity exoskeleton is a device for auxiliary assistance of human movement. The interaction performance between the exoskeleton and the human is determined by the lower extremity exoskeleton’s controller. The performance of the controller is affected by the accuracy of the dynamic equation. Therefore, it is necessary to study the dynamic parameter identification of lower extremity exoskeleton. The existing dynamic parameter identification algorithms for lower extremity exoskeletons are generally based on Least Square (LS). There are some internal drawbacks, such as complicated expe

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Wang, Xinyu, Shifeng Ou, and Ying Gao. "Convex Regularized Recursive Minimum Error Entropy Algorithm." Electronics 13, no. 5 (2024): 992. http://dx.doi.org/10.3390/electronics13050992.

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It is well known that the recursive least squares (RLS) algorithm is renowned for its rapid convergence and excellent tracking capability. However, its performance is significantly compromised when the system is sparse or when the input signals are contaminated by impulse noise. Therefore, in this paper, the minimum error entropy (MEE) criterion is introduced into the cost function of the RLS algorithm in this paper, with the aim of counteracting the interference from impulse noise. To address the sparse characteristics of the system, we employ a universally applicable convex function to regul

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38

Li, Hongxin, and Cangpu Wu. "New Algorithm for Parameter Identification Based on the RLS Algorithm." IFAC Proceedings Volumes 27, no. 8 (1994): 1369–74. http://dx.doi.org/10.1016/s1474-6670(17)47901-8.

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39

Akhtar, Muhammad Tahir. "Developing a New Filtered-X Recursive Least Squares Adaptive Algorithm Based on a Robust Objective Function for Impulsive Active Noise Control Systems." Applied Sciences 13, no. 4 (2023): 2715. http://dx.doi.org/10.3390/app13042715.

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It is well-known that performance of the classical algorithms for active noise control (ANC) systems severely degrades when implemented for controlling the impulsive sources. The objective of this paper is to propose a new recursive least squares (RLS) algorithm (and its variant) for being implemented in the framework of ANC systems. The proposed RLS-based adaptive algorithm employs an objective function designed to achieve robustness against the impulse type sources. The derivation of the algorithm is quite straightforward; however, a few modifications have been incorporated to address the ap

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40

Ardalan, S. H., and L. J. Faber. "A fast ARMA transversal RLS filter algorithm." IEEE Transactions on Acoustics, Speech, and Signal Processing 36, no. 3 (1988): 349–58. http://dx.doi.org/10.1109/29.1531.

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So, C. F., S. C. Ng, and S. H. Leung. "Gradient based variable forgetting factor RLS algorithm." Signal Processing 83, no. 6 (2003): 1163–75. http://dx.doi.org/10.1016/s0165-1684(03)00037-9.

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42

Sakai, Hideaki, and Hiroshi Nakaoka. "A fast sliding window QRD-RLS algorithm." Signal Processing 78, no. 3 (1999): 309–19. http://dx.doi.org/10.1016/s0165-1684(99)00071-7.

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43

Pyo, Younghun, Kyunghyun Lee, and Kwanho You. "Epicenter Localization using RDOA based RLS Algorithm." Universal Journal of Mechanical Engineering 5, no. 1 (2017): 20–23. http://dx.doi.org/10.13189/ujme.2017.050104.

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Guan, Qing Yang, Xuan Li, and Xiao Yu Lan. "An Improved Frequency Offset Cancellation for Uplink Multi-User OFDMA System Based on TF-RLS Algorithm." Applied Mechanics and Materials 577 (July 2014): 1004–7. http://dx.doi.org/10.4028/www.scientific.net/amm.577.1004.

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Time and frequency recursive least squares algorithm (TF-RLS) is proposed to cancel the interference due to the frequency offset (FO) in uplink Orthogonal Frequency Division Multiple Access (OFDMA) system. TF-RLS algorithm is composed of two stages, which is TD-RLS scheme and FD-RLS scheme. In the first stage, TD-RLS scheme is selected to pre-cancel the frequency offset in the time domain, and then the interference induced by residual frequency offset has been eliminated by the FD-RLS scheme in the frequency domain. The result of bit error rate (BER) shows that its performance is robust for ca

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Santucci, Valentino. "An Iterative Optimization Algorithm for Planning Spacecraft Pathways Through Asteroids." Applied Sciences 14, no. 23 (2024): 10987. http://dx.doi.org/10.3390/app142310987.

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In this article, we explore the use of meta-heuristic algorithms for costly black-box permutation optimization problems. These combinatorial problems are defined by solution spaces that consist of permutations of elements, with an objective function that lacks a closed mathematical representation and is expensive to evaluate. The focus of our investigation is the Asteroid Routing Problem (ARP), which seeks to determine the optimal sequence of asteroids to be visited by a spacecraft while minimizing energy consumption and travel time. Specifically, we assess the performance of a simple algorith

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Zheng, Xiao Zhe, Yu Hao Liu, and Cui Gai Lv. "Research on Anti-Jamming Algorithm Based on Beidou Satellite Navigation System." Applied Mechanics and Materials 380-384 (August 2013): 4128–31. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.4128.

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According to the four array elements of Beidou satellite navigation model as the research object, put forward a kind of Compass satellite navigation signal model construction method, and using Matlab software to build the satellite navigation signal system model . Based on the power inversion principle, try to use the recursive least squares (RLS) algorithm for getting the power inversion Optimum weights, compared and evaluated in terms of this performance. The results show that the power inversion based on RLS algorithm can make the antenna array in the direction of interference to automatica

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Mukhamadiev, Semen, Eugeniy Rogozhnikov, Edgar Dmitriyev, et al. "Method for Digital Cancellation of System Interference in a Full-Duplex Power Line Communication System." Electronics 12, no. 10 (2023): 2211. http://dx.doi.org/10.3390/electronics12102211.

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Every year the number of IoT devices is growing, which gives a boost to development of such technology as Power Line Communication (PLC). The term PLC refers to the use of a power supply circuit to transmit data. Full-duplex technology can be applied to increase the data transfer rate in a PLC. The difficulty in using a full duplex is the need to suppress the transmitter’s own signal (interference signal). Analog cancellation and digital cancellation are used for this purpose. Common algorithms for digital cancellation are adaptive algorithms. In this paper adaptive algorithms such as Particle

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Sun, HY, and SY Li. "RLS Channel Estimation Combined with Channel Equalization in Oversampled Frequency Domain for FBMC-QAM Systems." Journal of Physics: Conference Series 2476, no. 1 (2023): 012046. http://dx.doi.org/10.1088/1742-6596/2476/1/012046.

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Abstract In order to reduce the bit error rate and improve the anti-interference performance, this paper proposes a channel estimation algorithm based on RLS. RLS channel estimation algorithm obtains the current estimation data by modifying the final estimation data. First, the first data is estimated by least squares (LS), and then the date is adjusted in real time through forgetting factor and recursive formula to obtain all estimated data. The results show that RLS channel estimation algorithm can reduce the computation, improve the accuracy of channel estimation, and suppress noise interfe

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Tan, Si Wei, and Zhi Liang Ren. "Optimization on Tracking Performance of RLS Algorithm Using Transfer Function of Butterworth Low Pass Filter." Advanced Materials Research 850-851 (December 2013): 856–59. http://dx.doi.org/10.4028/www.scientific.net/amr.850-851.856.

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In order to get further optimizations on tracking performance of the RLS algorithm in nonstationarity signal processing, and to simplify the variable forgetting factor updating model, a novel variable forgetting factor updating model based on Butterworth low pass filter transfer function was proposed. The relationship between the variable forgetting factor and the tracking performance of RLS algorithm was analyzed. The updating model proposed in this paper was built based on the modification of the transfer function of Butterworth low pass filter. The model function fit the theoretical variati

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Wang, Lei, Kean Chen, Jian Xu, and Wang Qi. "Simplified fast transversal filter algorithms for multichannel active noise control." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 2 (2021): 4683–91. http://dx.doi.org/10.3397/in-2021-2793.

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In recent years, more attention has been paid to the performance of algorithm in active noise control (ANC). Compared with filtered-x LMS (FxLMS) algorithm based on stochastic gradient descent, filtered-x RLS (FXRLS) algorithm has faster convergence speed and better tracking performance at the cost of high computational complexity. In order to reduce the computation, fast transversal filter (FTF) algorithm can be used in ANC system. In this paper, simplified multi-channel FXFTF algorithms are presented, and the convergence speed and noise reduction performance of different multichannel algorit

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