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Journal articles on the topic 'Algoritmo RLS'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 February 2022

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1

Piccardi, M., M. Balzarini, G. A. Bó, and A. Capitaine Funes. "Asociación entre las características morfológicas y la producción de leche en vacas Holstein." Revista Veterinaria 23, no. 2 (2012): 134. http://dx.doi.org/10.30972/vet.2321793.

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<p>El objetivo de este estudio fue identificar las características morfológicas de tipo que contribuyen a explicar la variación de la producción en vacas Holstein. Se calificaron morfométricamente 1.290 vacas de la raza Holstein de cuatro tambos comerciales de la Provincia de Buenos Aires (Argentina). Los 15 caracteres morfológicos calificados fueron: inserción anterior de ubre (FU); altura de ubre posterior (RUH); ancho ubre posterior (RUW); ligamento suspensorio medio (UC); profundidad de la ubre (UD); colocación de pezones posterior (TP); longitud de los pezones (TL); estatura (ST); a

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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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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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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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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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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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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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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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9

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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10

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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11

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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12

Eksioglu, Ender M. "Group sparse RLS algorithms." International Journal of Adaptive Control and Signal Processing 28, no. 12 (2013): 1398–412. http://dx.doi.org/10.1002/acs.2449.

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13

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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14

Hassan, Ahmad Kamal, and Adnan Affandi. "On Modelling and Comparative Study of LMS and RLS Algorithms for Synthesis of MSA." Modelling and Simulation in Engineering 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/9742483.

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This paper deals with analytical modelling of microstrip patch antenna (MSA) by means of artificial neural network (ANN) using least mean square (LMS) and recursive least square (RLS) algorithms. Our contribution in this work is twofold. We initially provide a tutorial-like exposition for the design aspects of MSA and for the analytical framework of the two algorithms while our second aim is to take advantage of high nonlinearity of MSA to compare the effectiveness of LMS and that of RLS algorithms. We investigate the two algorithms by using gradient decent optimization in the context of radia

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15

Khonturaev, Ikrom, Mansur Khasanov, Muhiddin Anarbaev, Abror Kurbanov, Anvar Suyarov, and Urinboy Jalilov. "Atom Search Optimization Algorithm for Allocating Distributed Generators in Radial Distribution Systems." E3S Web of Conferences 264 (2021): 04084. http://dx.doi.org/10.1051/e3sconf/202126404084.

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In recent years the use of renewable energy sources (RES) by many power grid companies worldwide has increased significantly. The trend towards RES use is mainly due to environmental issues and rising fuel prices associated with conventional electricity generation. This paper introduces a hybrid approach to find the optimal location and size of distributed generations (DG) in the radial distribution system (RDS). The proposed approach is based on the atom search optimization (ASO) technique to calculate the optimal allocation of DGs and power loss sensitivity (PLS) index to obtain the best bus

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16

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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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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18

Hao, Yan Ling, Jun Wei Yang, Liang Chen, and Jin Hui Hao. "Research on Random Drift Modeling and Error Compensation Method for MEMS Gyroscope." Advanced Materials Research 466-467 (February 2012): 925–29. http://dx.doi.org/10.4028/www.scientific.net/amr.466-467.925.

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This paper presents modeling random drift by traditional time series method. In the modeling process, the real time average algorithm is proposed which can extract the constant drift of the MEMS gyroscope effectively to get random drift, and a modified recursive extended least squares (RELS) method for parameter estimation of the autoregressive moving average models (ARMA) is presented. The modified RELS algorithm consists of two-stage RLS algorithm which can on line be implemented, and has the fast convergence rate. After modeling, the corresponding Kalman filter is designed to make compensat

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SHINNAKA, Shinji. "Exponential Convergence of RLS Adaptive Algorithms." Transactions of the Society of Instrument and Control Engineers 24, no. 12 (1988): 1334–36. http://dx.doi.org/10.9746/sicetr1965.24.1334.

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20

Yu, H. F., E. H. K. Fung, and X. J. Jing. "An Improved ZMP-Based CPG Model of Bipedal Robot Walking Searched by SaDE." ISRN Robotics 2014 (March 4, 2014): 1–16. http://dx.doi.org/10.1155/2014/241767.

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This paper proposed a method to improve the walking behavior of bipedal robot with adjustable step length. Objectives of this paper are threefold. (1) Genetic Algorithm Optimized Fourier Series Formulation (GAOFSF) is modified to improve its performance. (2) Self-adaptive Differential Evolutionary Algorithm (SaDE) is applied to search feasible walking gait. (3) An efficient method is proposed for adjusting step length based on the modified central pattern generator (CPG) model. The GAOFSF is modified to ensure that trajectories generated are continuous in angular position, velocity, and accele

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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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22

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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23

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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24

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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25

Li, Tian-shu, Kai Tian, and Wen-xiu Li. "Method for improving RLS algorithms." Journal of Marine Science and Application 6, no. 3 (2007): 68–70. http://dx.doi.org/10.1007/s11804-007-5077-x.

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26

Ebrahimzadeh, Elias, Mohammad Pooyan, Sahar Jahani, Ahmad Bijar, and Seyed Kamal Setaredan. "ECG SIGNALS NOISE REMOVAL: SELECTION AND OPTIMIZATION OF THE BEST ADAPTIVE FILTERING ALGORITHM BASED ON VARIOUS ALGORITHMS COMPARISON." Biomedical Engineering: Applications, Basis and Communications 27, no. 04 (2015): 1550038. http://dx.doi.org/10.4015/s1016237215500386.

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The electrocardiogram (ECG) is generally used for the diagnosis of cardiovascular diseases. In many of the biomedical applications, it is necessary to remove the noise from ECG recordings. Several adaptive filter structures have been proposed for noise cancellation. Compared to the least mean square (LMS) method, the unbiased and normalized adaptive noise reduction (UNANR) algorithm has better performance, as mentioned in previous investigations. In this paper, we review various kinds of ECG noise reduction algorithms. To provide a detailed and fair comparison, all normalized LMS (NLMS), Block

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Li, Yin Xue, Jun Zhang, and Yong Feng Zhi. "Study on UWB Channel Equalization with Adaptive Gain Affine Projection Algorithm." Applied Mechanics and Materials 220-223 (November 2012): 2121–28. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.2121.

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A new equalization technology study with adaptive affine projection algorithm, aiming at the inter symbol interferences in the UWB channels was presented specially for time-hopping UWB (TH-UWB) systems. The computational complexity and convergence rate of the APA-AG algorithm was compared with the traditional algorithms. The simulation results show that this method improves the convergence rate and has a good stability. And the equalizer with the affine projection algorithm using adaptive gain is better than the RLS equalizer and the LMS equalizer.

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TABUCHI, Toshiaki, Nanayo FURUMOTO, Jiro MORIMOTO, Yoshikazu YAMAMOTO, and Ikunori KOBAYASHI. "Asymptotically Optimal RLS Adaptive Identification Algorithms." Transactions of the Institute of Systems, Control and Information Engineers 13, no. 1 (2000): 1–13. http://dx.doi.org/10.5687/iscie.13.1.

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Binde, S. "Stabilizing fast RLS algorithms by leakage." Signal Processing 70, no. 1 (1998): 1–21. http://dx.doi.org/10.1016/s0165-1684(98)00110-8.

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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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32

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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Alam, Mahbubul, Md Imdadul Islam, and M. R. Amin. "Performance Comparison of STFT, WT, LMS and RLS Adaptive Algorithms in Denoising of Speech Signal." International Journal of Engineering and Technology 3, no. 3 (2011): 235–38. http://dx.doi.org/10.7763/ijet.2011.v3.230.

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Djigan, Victor I. "Multichannel parallelizable sliding window RLS and fast RLS algorithms with linear constraints." Signal Processing 86, no. 4 (2006): 776–91. http://dx.doi.org/10.1016/j.sigpro.2005.06.010.

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35

Hassan, Mohamed H., Salah Kamel, Ali Selim, Tahir Khurshaid, and José Luis Domínguez-García. "A Modified Rao-2 Algorithm for Optimal Power Flow Incorporating Renewable Energy Sources." Mathematics 9, no. 13 (2021): 1532. http://dx.doi.org/10.3390/math9131532.

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In this paper, a modified Rao-2 (MRao-2) algorithm is proposed to solve the problem of optimal power flow (OPF) in a power system incorporating renewable energy sources (RES). Quasi-oppositional and Levy flight methods are used to improve the performance of the Rao algorithm. To demonstrate effectiveness of the MRao-2 technique, it is tested on two standard test systems: an IEEE 30-bus system and an IEEE 118-bus system. The objective function of the OPF is the minimization of fuel cost in five scenarios. The IEEE 30-bus system reflects fuel cost minimization in three scenarios (without RES, wi

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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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Sun, Gengxin, and Chih-Cheng Chen. "Influence Maximization Algorithm Based on Reverse Reachable Set." Mathematical Problems in Engineering 2021 (July 27, 2021): 1–12. http://dx.doi.org/10.1155/2021/5535843.

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Most of the existing influence maximization algorithms are not suitable for large-scale social networks due to their high time complexity or limited influence propagation range. Therefore, a D-RIS (dynamic-reverse reachable set) influence maximization algorithm is proposed based on the independent cascade model and combined with the reverse reachable set sampling. Under the premise that the influence propagation function satisfies monotonicity and submodularity, the D-RIS algorithm uses an automatic debugging method to determine the critical value of the number of reverse reachable sets, which

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Pratiwi, Nor Kumalasari Caecar, Rita Magdalena, Yunendah Nur Fuadah, Sofia Saidah, Syamsul Rizal, and Muhamad Rokhmat Isnaini. "Denoising Sinyal EEG dengan Algoritma Recursive Least Square dan Least Mean Square." TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol 5, no. 2 (2019): 122–29. http://dx.doi.org/10.15575/telka.v5n2.122-129.

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EEG mengukur fluktuasi tegangan yang dihasilkan dari arus ionik yang beredar sepanjang neuron otak. Dalam pengaturan eksperimental, sinyal EEG sering terkontaminasi dengan berbagai noise akibat gerakan otot dan jantung. Noise dengan magnitudo yang lebih tinggi dari sinyal aslinya akan merusak sinyal EEG dan bisa berakibat fatal dalam analisis diagnosa. Sehingga diperlukan sebuah sistem denoising yang mampu secara maksimal mengurangi noise, tanpa menghilangkan komponen informasi penting dari sinyal EEG. Salah satu algoritma yang dapat digunakan dalam mereduksi noise pada sinyal biomedis adalah

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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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Martinek, Radek, Jaroslav Rzidky, Rene Jaros, Petr Bilik, and Martina Ladrova. "Least Mean Squares and Recursive Least Squares Algorithms for Total Harmonic Distortion Reduction Using Shunt Active Power Filter Control." Energies 12, no. 8 (2019): 1545. http://dx.doi.org/10.3390/en12081545.

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This paper deals with the use of least mean squares (LMS, NLMS) and recursive least squares (RLS) algorithms for total harmonic distortion (THD) reduction using shunt active power filter (SAPF) control. The article presents a pilot study necessary for the construction of our own controlled adaptive modular inverter. The objective of the study is to find an optimal algorithm for the implementation. The introduction contains a survey of the literature and summarizes contemporary methods. According to this research, only adaptive filtration fulfills our requirements (adaptability, real-time proce

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Chen, Binhui, Rong Qu, Ruibin Bai, and Wasakorn Laesanklang. "A variable neighborhood search algorithm with reinforcement learning for a real-life periodic vehicle routing problem with time windows and open routes." RAIRO - Operations Research 54, no. 5 (2020): 1467–94. http://dx.doi.org/10.1051/ro/2019080.

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This paper studies a real-life container transportation problem with a wide planning horizon divided into multiple shifts. The trucks in this problem do not return to depot after every single shift but at the end of every two shifts. The mathematical model of the problem is first established, but it is unrealistic to solve this large scale problem with exact search methods. Thus, a Variable Neighbourhood Search algorithm with Reinforcement Learning (VNS-RLS) is thus developed. An urgency level-based insertion heuristic is proposed to construct the initial solution. Reinforcement learning is th

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Janapati, Ravichander, Ch Balaswamy, and K. Soundararajan. "Localization of Cooperative WSN using Distributed PSO with Optimum References." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 6 (2016): 3094. http://dx.doi.org/10.11591/ijece.v6i6.11427.

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<p>In indoor environment WSN nodes are deployed randomly and do not know the accurate position. Find the node position with the help of anchor nodes is known as localization. CRB algorithm selects the best anchor nodes which gives high accuracy. In this paper distributed PSO algorithm with optimum selection of reference nodes using CRB is proposed to find accurate node position. The proposed method performs better in comparison with other algorithms like PSO, RLS, LMS and GPS in terms of position accuracy, latency and complexity.</p>

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Janapati, Ravichander, Ch Balaswamy, and K. Soundararajan. "Localization of Cooperative WSN using Distributed PSO with Optimum References." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 6 (2016): 3094. http://dx.doi.org/10.11591/ijece.v6i6.pp3094-3102.

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<p>In indoor environment WSN nodes are deployed randomly and do not know the accurate position. Find the node position with the help of anchor nodes is known as localization. CRB algorithm selects the best anchor nodes which gives high accuracy. In this paper distributed PSO algorithm with optimum selection of reference nodes using CRB is proposed to find accurate node position. The proposed method performs better in comparison with other algorithms like PSO, RLS, LMS and GPS in terms of position accuracy, latency and complexity.</p>

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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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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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Abstract:

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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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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Carini, Alberto, and Enzo Mumolo. "Fast square-root RLS adaptive filtering algorithms." Signal Processing 57, no. 3 (1997): 233–50. http://dx.doi.org/10.1016/s0165-1684(97)00006-6.

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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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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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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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