Relevant bibliographies by topics / Filtros de Savitzky-Golay

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  2. Dissertations / Theses
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Academic literature on the topic 'Filtros de Savitzky-Golay'

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Published: 4 June 2021
Last updated: 11 February 2022

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Journal articles on the topic "Filtros de Savitzky-Golay"

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Melo Junior, Gilberto de, Sílvio Leão Vieira, Geovanne Pereira Furriel, Renato Milhomem de Oliveira Filho, Brunna Carolinne Rocha Silva, and Jane Sousa Naves. "Pré-processamento de sinais Eletro-oculográficos (EOG)." Research, Society and Development 10, no. 4 (April 10, 2021): e28410414221. http://dx.doi.org/10.33448/rsd-v10i4.14221.

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Este trabalho visa estudar sinais eletrooculográficos (EOG) provenientes da aquisição, incluindo janelamento, e aplicação de filtros digitais para processamento e análise. EOG é um sinal que mede e registra o potencial de repouso da retina do olho. Aqui, desenvolvemos um algoritmo para detectar sinais de movimento do globo ocular relativos a eletrodos fixados na face. Os sinais bioelétricos foram coletados de 40 voluntários adultos saudáveis. A metodologia aplicada segue as normas e diretrizes internacionais para aquisição de dados de sinais de ECG e com a anuência do Comitê de Ética em Pesquisa institucional. Dois filtros digitais Savitzky-Golay (SG) e Median Filter (FM), foram comparados. Como resultado, foram desenvolvidos e registrados softwares para janelamento de sinais e comparação entre filtros digitais, sendo o Savitzky-Golay o mais adequado para uso com EOG.
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Fearn, Tom. "Savitzky—Golay Filters." NIR news 11, no. 6 (December 2000): 14–15. http://dx.doi.org/10.1255/nirn.593.

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Press, William H., and Saul A. Teukolsky. "Savitzky-Golay Smoothing Filters." Computers in Physics 4, no. 6 (1990): 669. http://dx.doi.org/10.1063/1.4822961.

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Krishnan, Sunder Ram, and Chandra Sekhar Seelamantula. "On the Selection of Optimum Savitzky-Golay Filters." IEEE Transactions on Signal Processing 61, no. 2 (January 2013): 380–91. http://dx.doi.org/10.1109/tsp.2012.2225055.

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Quan, Quan, and Kai-Yuan Cai. "Time-domain analysis of the Savitzky–Golay filters." Digital Signal Processing 22, no. 2 (March 2012): 238–45. http://dx.doi.org/10.1016/j.dsp.2011.11.004.

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Sivagami, A. Vaishali, Ramya Ramakrishnan, and A. Subasini. "Weather Prediction Model using Savitzky-Golay and Kalman Filters." Procedia Computer Science 165 (2019): 449–55. http://dx.doi.org/10.1016/j.procs.2020.01.005.

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Niedźwiecki, Maciej, and Marcin Ciołek. "Generalized Savitzky–Golay filters for identification of nonstationary systems." Automatica 108 (October 2019): 108477. http://dx.doi.org/10.1016/j.automatica.2019.06.029.

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Schulze, H. Georg, Rod B. Foist, Andre Ivanov, and Robin F. B. Turner. "Fully Automated High-Performance Signal-to-Noise Ratio Enhancement Based on an Iterative Three-Point Zero-Order Savitzky—Golay Filter." Applied Spectroscopy 62, no. 10 (October 2008): 1160–66. http://dx.doi.org/10.1366/000370208786049079.

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The automated processing of data from high-throughput and real-time collection procedures is becoming a pressing problem. Currently the focus is shifting to automated smoothing techniques where, unlike background subtraction techniques, very few methods exist. We have developed a filter based on the widely used and conceptually simple moving average method or zero-order Savitzky–Golay filter and its iterative relative, the Kolmogorov–Zurbenko filter. A crucial difference, however, between these filters and our implementation is that our fully automated smoothing filter requires no parameter specification or parameter optimization. Results are comparable to, or better than, Savitzky–Golay filters with optimized parameters and superior to the automated iterative median filter. Our approach, because it is based on the highly familiar moving average concept, is intuitive, fast, and straightforward to implement and should therefore be of immediate and considerable practical use in a wide variety of spectroscopy applications.
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Nozato, Hideaki, Thomas Bruns, Henrik Volkers, and Akihiro Oota. "A study of Savitzky-Golay filters for derivatives in primary shock calibration." ACTA IMEKO 2, no. 2 (January 15, 2014): 41. http://dx.doi.org/10.21014/acta_imeko.v2i2.62.

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This manuscript reports the result of an investigation into two types of digital filters for numerical differentiation of the displacement signal in the case of primary shock calibration of accelerometers. The first is a difference method with a 4<sup>th</sup>-order Butterworth low-pass (4<sup>th</sup> BW) filter; the other is a Savitzky-Golay (S-G) filter, which applies a moving polynomial approximation. The computational comparison was applied to low and high amplitude shocks using known excitation functions. Each sum of residuals was compared for the optimized conditions of the 4<sup>th</sup> BW and S-G filters. The results of computer simulation indicated that the S-G filters exhibited better performance for the derivatives than the 4<sup>th</sup> BW filters. In addition, an analytical comparison using experimental vibration data also indicated that the S-G filters exhibited better derivative characteristics than the 4<sup>th</sup> BW filters.<br />
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Candan, Çağatay, and Hakan Inan. "A unified framework for derivation and implementation of Savitzky–Golay filters." Signal Processing 104 (November 2014): 203–11. http://dx.doi.org/10.1016/j.sigpro.2014.04.016.

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Dissertations / Theses on the topic "Filtros de Savitzky-Golay"

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FIGUEIREDO, Natanael de Souza. "Aplicação de filtros de Savitzky-Golay no processamento de sinais de eletrocardiografia." reponame:Repositório Institucional da UNIFEI, 2018. http://repositorio.unifei.edu.br/xmlui/handle/123456789/1562.

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Submitted by repositorio repositorio (repositorio@unifei.edu.br) on 2018-08-20T20:24:12Z No. of bitstreams: 1 dissertacao_2018114.pdf: 2629788 bytes, checksum: 96c2038f09c7afab9160c2c52629fc8d (MD5)
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O presente trabalho é parte do projeto FINEP sob o convênio 01.13.0387, cujo objetivo global é a construção de um microssistema de eletrocardiografia de baixo custo para monitoramento remoto. Neste contexto, o objetivo específico deste trabalho é projetar filtros digitais diferenciadores, baseados na técnica dos mínimos quadrados de Savitzky-Golay, capazes de eliminar ruídos provenientes das interferências de alta frequência e também da rede elétrica, para melhorar confiabilidade das medidas, mantendo o projeto comprometido com as normas técnicas aplicáveis e com o baixo custo. As novas abordagens mantêm as mesmas propriedades da abordagem clássica, porém resultam em filtros com menor amplificação de ruído.
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Schettino, Bruno Montesano. "Método para detecção e compensação dos efeitos causados pela saturação dos TCs de proteção com meios adaptativos para mitigação da influência do ruído e dos desvios de frequência." Universidade Federal de Juiz de Fora, 2015. https://repositorio.ufjf.br/jspui/handle/ufjf/1142.

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Este trabalho propõe um método para detectar a saturação dos núcleos dos transformadores de corrente (TCs) utilizados na proteção de sistemas elétricos de potência (SEPs), além de promover a compensação de seus efeitos através da correção do sinal de corrente secundária distorcido pela saturação. Técnicas de processamento de sinais baseadas no filtro diferenciador de segunda ordem de Savitzky-Golay são utilizadas para localizar os pontos de transição entre partes do sinal de corrente distorcidas e não distorcidas pela saturação. Em seguida, um processo de estimação baseado no critério dos mínimos quadrados que utiliza exclusivamente amostras do sinal contidas nas regiões não distorcidas é efetuado, extraindo os parâmetros necessários à promoção da correção do sinal. As influências do ruído e dos desvios de frequência de operação do SEP foram analisadas, tendo sido desenvolvidos e incorporados meios adaptativos para mitigar seus efeitos. Os algoritmos desenvolvidos foram implementados em MATLAB e a avaliação de desempenho foi realizada utilizando sinais extraídos de simulações de falta ocorridas em um sistema modelado em um simulador digital em tempo real (RTDS). Os resultados indicaram que o método proposto atingiu desempenho satisfatório, independente dos parâmetros do TC e dentro de uma ampla gama de cenários da falta analisados. Além disso, o método mostrou-se robusto em relação ao ruído e eficiente na mitigação dos erros provocados pelos desvios de frequência. Ainda, os recursos técnicos e computacionais necessários para sua execução indicam que o método proposto é passível de implementação nos atuais dispositivos de proteção disponibilizados pela indústria.
This work proposes a method for detecting the saturation of the current-transformer cores used in the protection of electric power systems and promote the compensation for its effects by correcting the secondary current signal distorted due to the saturation. Signal processing techniques based on the second order differentiator Savitzky-Golay filter are used for locating the transition points between distorted and undistorted parts of the current signal. Then, an estimation process based on the least squares criteria that uses exclusively signal samples included in the undistorted regions is performed, extracting the parameters needed for the signal correction. The influences of the noise and the frequency offset were analysed, and adaptive means to mitigate their effects were developed and incorporated. The developed algorithms were implemented in MATLAB and performance evaluation was performed using the signals taken from fault simulations in a system modeled on a real time digital simulator (RTDS). The results indicated that the proposed method reaches a satisfactory performance, regardless of the CT parameters and within a wide range of analysed fault scenarios. Moreover, the method showed to be robust relative to the noise and effective in mitigating the errors due to the frequency offsets.
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FERNANDES, Bruna de Almeida. "Utilização do Filtro de Savitzky-Golay no cancelamento de interferência de 60-Hz em sinais de Eletrocardiograma." reponame:Repositório Institucional da UNIFEI, 2017. http://repositorio.unifei.edu.br:8080/xmlui/handle/123456789/716.

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Esta dissertação apresenta a utilização do filtro de Savitzky-Golay no cancelamento de interferências de 60-Hz em sinais de eletrocardiograma. Um filtro de Savitzky-Golay com janela de onze amostras e polinômio de sétima ordem, operando com uma taxa de amostragem de 192-Hz, possibilita o casamento da frequência de primeiro nulo espectral em 60-Hz para uma banda passante de 40-Hz, satisfazendo a norma ABNT NBR IEC 60601-2-27:2013. A simplicidade aritmética e a utilização de poucos coeficientes inteiros permite que o filtro seja implementado em microcontroladores de baixo custo presentes em sistemas de monitoramento remoto.
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Menon, Seeram V. "Savitzky-Golay Filters and Application to Image and Signal Denoising." Thesis, 2015. http://etd.iisc.ernet.in/2005/3844.

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We explore the applicability of local polynomial approximation of signals for noise suppression. In the context of data regression, Savitzky and Golay showed that least-squares approximation of data with a polynomial of fixed order, together with a constant window length, is identical to convolution with a finite impulse response filter, whose characteristics depend entirely on two parameters, namely, the order and window length. Schafer’s recent article in IEEE Signal Processing Magazine provides a detailed account of one-dimensional Savitzky-Golay (SG) filters. Drawing motivation from this idea, we present an elaborate study of two-dimensional SG filters and employ them for image denoising by optimizing the filter response to minimize the mean-squared error (MSE) between the original image and the filtered output. The key contribution of this thesis is a method for optimal selection of order and window length of SG filters for denoising images. First, we apply the denoising technique for images contaminated by additive Gaussian noise. Owing to the absence of ground truth in practice, direct minimization of the MSE is infeasible. However, the classical work of C. Stein provides a statistical method to overcome the hurdle. Based on Stein’s lemma, an estimate of the MSE, namely Stein’s unbiased risk estimator (SURE), is derived, and the two critical parameters of the filter are optimized to minimize the cost. The performance of the technique improves when a regularization term, which penalizes fast variations in the estimate, is added to the optimization cost. In the next three chapters, we focus on non-Gaussian noise models. In Chapter 3, image degradation in the presence of a compound noise model, where images are corrupted by mixed Poisson-Gaussian noise, is addressed. Inspired by Hudson’s identity, an estimate of MSE, namely Poisson unbiased risk estimator (PURE), which is analogous to SURE, is developed. Combining both lemmas, Poisson-Gaussian unbiased risk estimator (PGURE) minimization is performed to obtain the optimal filter parameters. We also show that SG filtering provides better lowpass approximation for a multiresolution denoising framework. In Chapter 4, we employ SG filters for reducing multiplicative noise in images. The standard SG filter frequency response can be controlled along horizontal or vertical directions. This limits its ability to capture oriented features and texture that lie at other angles. Here, we introduce the idea of steering the SG filter kernel and perform mean-squared error minimization based on the new concept of multiplicative noise unbiased risk estimation (MURE). Finally, we propose a method to robustify SG filters, robustness to deviation from Gaussian noise statistics. SG filters work on the principle of least-squares error minimization, and are hence compatible with maximum-likelihood (ML) estimation in the context of Gaussian statistics. However, for heavily-tailed noise such as the Laplacian, where ML estimation requires mean-absolute error minimization in lieu of MSE minimization, standard SG filter performance deteriorates. `1 minimization is a challenge since there is no closed-form solution. We solve the problem by inducing the `1-norm criterion using the iteratively reweighted least-squares (IRLS) method. At every iteration, we solve an l`2 problem, which is equivalent to optimizing a weighted SG filter, but, as iterations progress, the solution converges to that corresponding to `1 minimization. The results thus obtained are superior to those obtained using the standard SG filter.
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Krishnan, Sunder Ram. "Optimum Savitzky-Golay Filtering for Signal Estimation." Thesis, 2013. http://hdl.handle.net/2005/3293.

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Motivated by the classic works of Charles M. Stein, we focus on developing risk-estimation frameworks for denoising problems in both one-and two-dimensions. We assume a standard additive noise model, and formulate the denoising problem as one of estimating the underlying clean signal from noisy measurements by minimizing a risk corresponding to a chosen loss function. Our goal is to incorporate perceptually-motivated loss functions wherever applicable, as in the case of speech enhancement, with the squared error loss being considered for the other scenarios. Since the true risks are observed to depend on the unknown parameter of interest, we circumvent the roadblock by deriving finite-sample un-biased estimators of the corresponding risks based on Stein’s lemma. We establish the link with the multivariate parameter estimation problem addressed by Stein and our denoising problem, and derive estimators of the oracle risks. In all cases, optimum values of the parameters characterizing the denoising algorithm are determined by minimizing the Stein’s unbiased risk estimator (SURE). The key contribution of this thesis is the development of a risk-estimation approach for choosing the two critical parameters affecting the quality of nonparametric regression, namely, the order and bandwidth/smoothing parameters. This is a classic problem in statistics, and certain algorithms relying on derivation of suitable finite-sample risk estimators for minimization have been reported in the literature (note that all these works consider the mean squared error (MSE) objective). We show that a SURE-based formalism is well-suited to the regression parameter selection problem, and that the optimum solution guarantees near-minimum MSE (MMSE) performance. We develop algorithms for both glob-ally and locally choosing the two parameters, the latter referred to as spatially-adaptive regression. We observe that the parameters are so chosen as to tradeoff the squared bias and variance quantities that constitute the MSE. We also indicate the advantages accruing out of incorporating a regularization term in the cost function in addition to the data error term. In the more general case of kernel regression, which uses a weighted least-squares (LS) optimization, we consider the applications of image restoration from very few random measurements, in addition to denoising of uniformly sampled data. We show that local polynomial regression (LPR) becomes a special case of kernel regression, and extend our results for LPR on uniform data to non-uniformly sampled data also. The denoising algorithms are compared with other standard, performant methods available in the literature both in terms of estimation error and computational complexity. A major perspective provided in this thesis is that the problem of optimum parameter choice in nonparametric regression can be viewed as the selection of optimum parameters of a linear, shift-invariant filter. This interpretation is provided by deriving motivation out of the hallmark paper of Savitzky and Golay and Schafer’s recent article in IEEE Signal Processing Magazine. It is worth noting that Savitzky and Golay had shown in their original Analytical Chemistry journal article, that LS fitting of a fixed-order polynomial over a neighborhood of fixed size is equivalent to convolution with an impulse response that is fixed and can be pre-computed. They had provided tables of impulse response coefficients for computing the smoothed function and smoothed derivatives for different orders and neighborhood sizes, the resulting filters being referred to as Savitzky-Golay (S-G) filters. Thus, we provide the new perspective that the regression parameter choice is equivalent to optimizing for the filter impulse response length/3dB bandwidth, which are inversely related. We observe that the MMSE solution is such that the S-G filter chosen is of longer impulse response length (equivalently smaller cutoff frequency) at relatively flat portions of the noisy signal so as to smooth noise, and vice versa at locally fast-varying portions of the signal so as to capture the signal patterns. Also, we provide a generalized S-G filtering viewpoint in the case of kernel regression. Building on the S-G filtering perspective, we turn to the problem of dynamic feature computation in speech recognition. We observe that the methodology employed for computing dynamic features from the trajectories of static features is in fact derivative S-G filtering. With this perspective, we note that the filter coefficients can be pre-computed, and that the whole problem of delta feature computation becomes efficient. Indeed, we observe an advantage by a factor of 104 on making use of S-G filtering over actual LS polynomial fitting and evaluation. Thereafter, we study the properties of first-and second-order derivative S-G filters of certain orders and lengths experimentally. The derivative filters are bandpass due to the combined effects of LPR and derivative computation, which are lowpass and highpass operations, respectively. The first-and second-order S-G derivative filters are also observed to exhibit an approximately constant-Q property. We perform a TIMIT phoneme recognition experiment comparing the recognition accuracies obtained using S-G filters and the conventional approach followed in HTK, where Furui’s regression formula is made use of. The recognition accuracies for both cases are almost identical, with S-G filters of certain bandwidths and orders registering a marginal improvement. The accuracies are also observed to improve with longer filter lengths, for a particular order. In terms of computation latency, we note that S-G filtering achieves delta and delta-delta feature computation in parallel by linear filtering, whereas they need to be obtained sequentially in case of the standard regression formulas used in the literature. Finally, we turn to the problem of speech enhancement where we are interested in de-noising using perceptually-motivated loss functions such as Itakura-Saito (IS). We propose to perform enhancement in the discrete cosine transform domain using risk-minimization. The cost functions considered are non-quadratic, and derivation of the unbiased estimator of the risk corresponding to the IS distortion is achieved using an approximate Taylor-series analysis under high signal-to-noise ratio assumption. The exposition is general since we focus on an additive noise model with the noise density assumed to fall within the exponential class of density functions, which comprises most of the common densities. The denoising function is assumed to be pointwise linear (modified James-Stein (MJS) estimator), and parallels between Wiener filtering and the optimum MJS estimator are discussed.
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Santos, Nuno Filipe Cruz. "Radial Basis Functions Based Identification of Longitudinal Flight Dynamic Model." Master's thesis, 2019. http://hdl.handle.net/10400.6/8490.

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In the present work two distinct methods for the identification of the longitudinal flight model, in the state-space representation, are presented. Firstly, this dissertation introduces the different steps that lead up to the development and attainment of the flight equations of motion for a generic aircraft. Next, the theoretical background on which both identification methods are based upon is presented. In order to describe the proposed methods a sufficiently generic commercial aircraft is considered, which model is known, so the validation of the proposed concepts may be performed. The results obtained show that both proposed identification methods successfully achieve the model of the chosen aircraft.
No presente trabalho são apresentados dois métodos distintos de identificação de modelos de voo longitudinal, na representação no espaço de estados. A dissertação começa por introduzir as diferentes etapas que levam ao desenvolvimento e obtenção das diferentes equações do movimento que regem o voo sob uma forma genérica. Seguidamente apresenta-se a teoria na qual os métodos de identificação assentam. De forma a ilustrar os métodos propostos consideram-se o caso de uma aeronave comercial, suficientemente genérica, com o modelo conhecido de modo a puder validar os conceitos apresentados. Os resultados obtidos mostraram que os métodos propostos conseguem identificar com sucesso o modelo da aeronave alvo.
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Book chapters on the topic "Filtros de Savitzky-Golay"

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Persson, Per-Olof, and Gilbert Strang. "Smoothing by Savitzky-Golay and Legendre Filters." In Mathematical Systems Theory in Biology, Communications, Computation, and Finance, 301–15. New York, NY: Springer New York, 2003. http://dx.doi.org/10.1007/978-0-387-21696-6_11.

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Kher, Vansha, Garvita Khajuria, Purnendu Prabhat, Meena Kohli, and Vinod K. Madan. "Application of Higham and Savitzky-Golay Filters to Nuclear Spectra." In Soft Computing Applications, 487–96. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62521-8_42.

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Uzinski, Julio Cezar, Bruno Rodrigues de Oliveira, and Caio Cesar Enside de Abreu. "Obtenção de Tendências em Série Temporal empregando a Transformada Wavelet e o filtro Savitzky-Golay." In Aplicações de inteligência artificial e ciência de dados, 7–23. Pantanal Editora, 2020. http://dx.doi.org/10.46420/9786588319260cap1.

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Conference papers on the topic "Filtros de Savitzky-Golay"

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Menon, Sreeram V., and Chandra Sekhar Seelamantula. "Robust Savitzky-Golay filters." In 2014 International Conference on Digital Signal Processing (DSP). IEEE, 2014. http://dx.doi.org/10.1109/icdsp.2014.6900752.

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Restrepo, Jose, Julio Viola, Flavio Quizhpi, and Antonio Ginart. "Fast detection of sequence components using Savitzky-Golay filters." In IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2014. http://dx.doi.org/10.1109/iecon.2014.7049173.

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Karaim, Malek, Aboelmagd Noureldin, and Tashfeen B. Karamat. "Low-cost IMU Data Denoising using Savitzky-Golay Filters." In 2019 International Conference on Communications, Signal Processing, and their Applications (ICCSPA). IEEE, 2019. http://dx.doi.org/10.1109/iccspa.2019.8713728.

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Schafer, Ronald W. "On the frequency-domain properties of Savitzky-Golay filters." In 2011 Digital Signal Processing and Signal Processing Education Meeting (DSP/SPE). IEEE, 2011. http://dx.doi.org/10.1109/dsp-spe.2011.5739186.

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Hargittai, S. "Savitzky-Golay least-squares polynomial filters in ECG signal processing." In Computers in Cardiology, 2005. IEEE, 2005. http://dx.doi.org/10.1109/cic.2005.1588216.

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Menon, Sreeram V., and Chandra Sekhar Seelamantula. "Sure-optimal two-dimensional Savitzky-Golay filters for image denoising." In 2013 20th IEEE International Conference on Image Processing (ICIP). IEEE, 2013. http://dx.doi.org/10.1109/icip.2013.6738095.

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Shekhar, Chandra. "On simplified application of multidimensional Savitzky-Golay filters and differentiators." In PROGRESS IN APPLIED MATHEMATICS IN SCIENCE AND ENGINEERING PROCEEDINGS. AIP Publishing LLC, 2016. http://dx.doi.org/10.1063/1.4940262.

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Tanu and Deepti Kakkar. "Accounting For Order-Frame Length Tradeoff of Savitzky-Golay Smoothing Filters." In 2018 5th International Conference on Signal Processing and Integrated Networks (SPIN). IEEE, 2018. http://dx.doi.org/10.1109/spin.2018.8474194.

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Renato Ribeiro Aleixo, Leandro Rodrigues Manso Silva, Max Mateus Luiz, Guilherme Gaudereto Sena, Carlos Augusto Duque, and Paulo Fernando Ribeiro. "Um método de estimação de frequência para PMUs utilizando filtro Savitzky-Golay." In XXII Congresso Brasileiro de Automática. Joao Pessoa, Paraíba, Brasil: SBA Sociedade Brasileira de Automática, 2018. http://dx.doi.org/10.20906/cps/cba2018-0069.

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Toonkum, Pollakrit, and Chedsada Chinrungrueng. "Speckle reduction of ultrasound images based on locally regularized Savitzky-Golay filters." In 2015 12th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON). IEEE, 2015. http://dx.doi.org/10.1109/ecticon.2015.7206979.

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