Academic literature on the topic 'Algoritmo RLS'

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Journal articles on the topic "Algoritmo RLS"

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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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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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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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Dissertations / Theses on the topic "Algoritmo RLS"

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Silva, Cristiane Cristina Sousa da. "UM ALGORITMO TIPO RLS BASEADO EM SUPERFÍCIES NÃO QUADRÁTICAS." Universidade Federal do Maranhão, 2013. http://tedebc.ufma.br:8080/jspui/handle/tede/550.

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Made available in DSpace on 2016-08-17T16:54:33Z (GMT). No. of bitstreams: 1 Tese Cristiane Cristina.pdf: 4404224 bytes, checksum: a68e5757bedc2d3d341a5937f100fe1f (MD5) Previous issue date: 2013-07-19<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior<br>In adaptive filtering many adaptive filter are based on the mean square error method (MSE). These filters were developed to improve convergence spedd with a lower misadjustment. The least mean square (LMS) and the recursive least square (RLS) algorithms have been the hallmark of adaptive filtering. In this work we develop adap
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Benetti, Tiago. "Estimativa robusta da frequ?ncia card?aca a partir de sinais de fotopletismografia de pulso." Pontif?cia Universidade Cat?lica do Rio Grande do Sul, 2018. http://tede2.pucrs.br/tede2/handle/tede/8337.

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Submitted by PPG Engenharia El?trica (engenharia.pg.eletrica@pucrs.br) on 2018-10-29T13:30:23Z No. of bitstreams: 1 TIAGO BENETTI_DIS.pdf: 5038519 bytes, checksum: 95fa8d1b367b574eee27e772a55a9a49 (MD5)<br>Approved for entry into archive by Caroline Xavier (caroline.xavier@pucrs.br) on 2018-10-30T17:21:55Z (GMT) No. of bitstreams: 1 TIAGO BENETTI_DIS.pdf: 5038519 bytes, checksum: 95fa8d1b367b574eee27e772a55a9a49 (MD5)<br>Made available in DSpace on 2018-10-30T17:27:25Z (GMT). No. of bitstreams: 1 TIAGO BENETTI_DIS.pdf: 5038519 bytes, checksum: 95fa8d1b367b574eee27e772a55a9a49 (MD5) Previous
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Sequeira, Armando M. P. de Jesus. "Adaptive two dimensional RLS algorithms." Thesis, Monterey, California. Naval Postgraduate School, 1989. http://hdl.handle.net/10945/25653.

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Brown, Andrew P., and Ronald A. Iltis. "DISTRIBUTED TERRESTRIAL RADIOLOCATION USING THE RLS ALGORITHM." International Foundation for Telemetering, 2002. http://hdl.handle.net/10150/605572.

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International Telemetering Conference Proceedings / October 21, 2002 / Town & Country Hotel and Conference Center, San Diego, California<br>This paper presents the development of two distributed terrestrial radiolocation algorithms that use range estimates derived from DS-CDMA waveforms. The first algorithm, which is RLS-based, is derived as the solution of an approximate least-squares positioning problem. This algorithm has the advantage of reduced computational complexity, compared with the EKF-based algorithm that is presented. It is shown via simulations that both positioning algorithm
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Maciel, Allan James Ferreira. "CONVERGÊNCIA DO ESTIMADOR RLS PARA ALGORITMOS DE PROGRAMAÇÃO DINÂMICA HEURÍSTICA." Universidade Federal do Maranhão, 2012. http://tedebc.ufma.br:8080/jspui/handle/tede/494.

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Made available in DSpace on 2016-08-17T14:53:22Z (GMT). No. of bitstreams: 1 Dissertacao Allan James.pdf: 3170694 bytes, checksum: 054a9e74e81a7c2099800246d0b6c530 (MD5) Previous issue date: 2012-09-28<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior<br>The union of methodologies for optimal control and dynamics programming has stimulated the development of algorithms for realization of discrete control systems of the type linear quadratic regulator (DLQR). The methodology is based on reinforcement learning methods based on temporal differences and approximate dynamic program
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Huo, Jia Q. "Numerical properties of adaptive recursive least-squares (RLS) algorithms with linear constraints." Curtin University of Technology, Australian Telecommunications Research Institute, 1999. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=10094.

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Adaptive filters have found applications in many signal processing problems. In some situations, linear constraints are imposed on the filter weights such that the filter is forced to exhibit a certain desired response. Several algorithms for linearly constrained least-squares adaptive filtering have been developed in the literature. When implemented with finite precision arithmetic, these algorithms are inevitably subjected to rounding errors. It is essential to understand how these algorithms react to rounding errors.In this thesis, the numerical properties of three linearly constrained leas
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Deyneka, Alexander. "Metody ekvalizace v digitálních komunikačních systémech." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2011. http://www.nusl.cz/ntk/nusl-218963.

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Tato práce je psaná v angličtině a je zaměřená na problematiku ekvalizace v digitálních komunikačních systémech. Teoretická část zahrnuje stručné pozorování různých způsobů návrhu ekvalizérů. Praktická část se zabývá implementací nejčastěji používaných ekvalizérů a s jejich adaptačními algoritmy. Cílem praktické části je porovnat jejich charakteristiky a odhalit činitele, které ovlivňují kvalitu ekvalizace. V rámci problematiky ekvalizace jsou prozkoumány tři typy ekvalizérů. Lineární ekvalizér, ekvalizér se zpětnou vazbou a ML (Maximum likelihood) ekvalizér. Každý ekvalizér byl testován na mo
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Krejča, Libor. "Implementace algoritmů ekvalizace přenosového kanálu v FMT modulaci." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2010. http://www.nusl.cz/ntk/nusl-218254.

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The objective of Diploma thesis is design of analysis tool for equalizers used in FMT modulation. The model of transmission channel was designed for simulations with FMT. The transmission path is modeled by test loop, which corresponds to DSL line. For this reason, some principles of DSL technology is described in the thesis. The principles of multicarrier modulation are introduced in first part. The multicarrier modulation with filter bank (FMT) is described in detail.The different methods of design the fiter bank are given and compared. Channel equalization are introduced in second part. The
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Karlsson, Erlendur. "Least squares arma modeling of linear time-varying systems : lattice filter structures and fast RLS algorithms." Diss., Georgia Institute of Technology, 1987. http://hdl.handle.net/1853/15936.

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Gramm, Jens. "Fixed-parameter algorithms for the consensus analysis of genomic data." [S.l. : s.n.], 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=973911271.

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Books on the topic "Algoritmo RLS"

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Armando M. P. de Jesus Sequeira. Adaptive two dimensional RLS algorithms. Naval Postgraduate School, 1989.

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Tobia, John. A time-varying analysis of the exponentially data weighted recursive least squares (EDW-RLS) algorithm. National Library of Canada, 1992.

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Book chapters on the topic "Algoritmo RLS"

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Ramirez, Paulo Sergio. "Fast Transversal RLS Algorithms." In The Kluwer International Series in Engineering and Computer Science. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-3637-3_7.

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Apolinário, José A., and Paulo S. R. Diniz. "Fast QRD-RLS Algorithms." In QRD-RLS Adaptive Filtering. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-09734-3_4.

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Rontogiannis, Athanasios A., and Sergios Theodoridis. "Householder-Based RLS Algorithms." In QRD-RLS Adaptive Filtering. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-09734-3_7.

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Diniz, Paulo S. R. "Fast Transversal Rls Algorithms." In Adaptive Filtering. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-68606-6_8.

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Diniz, Paulo S. R. "Fast Transversal RLS Algorithms." In Adaptive Filtering. Springer US, 2013. http://dx.doi.org/10.1007/978-1-4614-4106-9_8.

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Diniz, Paulo S. R. "Fast Transversal RLS Algorithms." In Adaptive Filtering. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29057-3_8.

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Diniz, Paulo Sergio Ramirez. "Fast Transversal RLS Algorithms." In Adaptive Filtering. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4419-8660-3_7.

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Ramirez, Paulo Sergio. "Adaptive Lattice-Based RLS Algorithms." In The Kluwer International Series in Engineering and Computer Science. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-3637-3_6.

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Ramos, António L. L., and Stefan Werner. "Multichannel Fast QRD-RLS Algorithms." In QRD-RLS Adaptive Filtering. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-09734-3_6.

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Diniz, Paulo S. R. "Adaptive Lattice-Based Rls Algorithms." In Adaptive Filtering. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-68606-6_7.

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Conference papers on the topic "Algoritmo RLS"

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Omar Alexander Chura Vilcanqui, Luiz Alberto Luz de Almeida, and Claudio José Bordin Júnior. "Amplificadores de Tensão e Corrente Para Testes de Relé com Controlador Estimado por Algoritmo RLS." In VI Simpósio Brasileiro de Sistemas Elétricos. Grupo de Pesquisa Otimização e Supervisão de Sistemas Elétricos Industriais – OSSEI, 2015. http://dx.doi.org/10.20906/cps/sbse2016-0391.

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DOS SANTOS RIBEIRO, ANTONIO HENRIQUE, Wilander Testone Pereira da Silva, Francisco das C. de Souza, João Fonseca Neto, and Raimundo Nonato Mendes Martins. "UM ALGORITMO RLS-LMS USANDO COMBINAÇÃO AFIM DE FILTROS ADAPTATIVOS PARA CONFORMAÇÃO DE FEIXE EM ANTENAS INTELIGENTES." In ANAIS DO 14º SIMPóSIO BRASILEIRO DE AUTOMAçãO INTELIGENTE. Galoa, 2019. http://dx.doi.org/10.17648/sbai-2019-111446.

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Qin, Zhen, Jun Tao, Liang An, Shuai Yao, and Xiao Han. "Fast Sparse RLS Algorithms." In 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP). IEEE, 2018. http://dx.doi.org/10.1109/wcsp.2018.8555873.

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Wilbanks, J. Justin, and Michael J. Leamy. "Uncertain Parameter Estimation Approaches for Increasing the Effectiveness of Command-Shaped Engine Restart Strategies." In ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/detc2017-67548.

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This paper develops recursive least-squares (RLS) and extended Kalman filtering (EKF) approaches for estimating uncertain engine friction (and other) parameters necessary for successful implementation of a two-scale command shaping (TSCS) engine restart strategy. The TSCS strategy has been developed for mitigating vibrations in conventional and hybrid electric vehicle (HEV) powertrains during internal combustion engine (ICE) restart. Implementing the TSCS strategy increases the drivability of a HEV by reducing noise, vibration, and harshness (NVH) issues associated with ICE restart during a po
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Elisei-Iliescu, Camelia, Cristian Stanciu, Constantin Paleologu, Jacob Benesty, Cristian Anghel, and Silviu Ciochina. "Robust variable-regularized RLS algorithms." In 2017 Hands-free Speech Communications and Microphone Arrays (HSCMA). IEEE, 2017. http://dx.doi.org/10.1109/hscma.2017.7895584.

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Bellizia, Davide, Pietro Monsurro, and Alessandro Trifiletti. "VHDL implementation of FWL RLS algorithm." In 2017 European Conference on Circuit Theory and Design (ECCTD). IEEE, 2017. http://dx.doi.org/10.1109/ecctd.2017.8093356.

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Te Yan Chen and Yuriy Zakharov. "Convergence analysis of RLS-DCD algorithm." In 2009 IEEE/SP 15th Workshop on Statistical Signal Processing (SSP). IEEE, 2009. http://dx.doi.org/10.1109/ssp.2009.5278616.

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Begusic, D., D. Linebarger, E. M. Dowling, and B. Raghothaman. "Spectral line RLS adaptive filtering algorithm." In 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258). IEEE, 1999. http://dx.doi.org/10.1109/icassp.1999.756208.

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Salmanpour, Aryan, Nikjoo S. Mohammad, Arash Saber Tehrani, and Seyed Mohammad Amin Moghadas. "Extraction of Fetal Electrocardiogram from Maternal Skin Electrodes using Affine Projection Algorithm (APA), Recursive Least Square (RLS), and QR-RLS Algorithms." In 2007 IEEE International Symposium on Signal Processing and Information Technology. IEEE, 2007. http://dx.doi.org/10.1109/isspit.2007.4458112.

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Martinek, Radek, Radana Kahankova, Jan Nedoma, Marcel Fajkus, and Michal Skacel. "Comparison of the LMS, NLMS, RLS, and QR-RLS algorithms for vehicle noise suppression." In the 10th International Conference. ACM Press, 2018. http://dx.doi.org/10.1145/3177457.3177502.

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Reports on the topic "Algoritmo RLS"

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Turner, Peter R. An Improved RNS Division Algorithm. Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada299006.

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