Academic literature on the topic 'Least Square Error'

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Journal articles on the topic "Least Square Error"

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Yonghe, Deng. "Improved Total Least Square Algorithm." Open Civil Engineering Journal 9, no. 1 (2015): 394–99. http://dx.doi.org/10.2174/1874149501509010394.

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Aim to blemish of total least square algorithm based on error equation of virtual observation,this paper proposed a sort of improved algorithm which doesn’t neglect condition equation of virtual observation,and considers both error equation and condition equation of virtual observation.So,the improved algorithm is better.Finally,this paper has fitted a straight line in three-dimensional space based on the improved algorithm.The result showed that the improved algorithm is viable and valid.
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Armentano, Marı́a G., and Ricardo G. Durán. "Error estimates for moving least square approximations." Applied Numerical Mathematics 37, no. 3 (2001): 397–416. http://dx.doi.org/10.1016/s0168-9274(00)00054-4.

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Zuppa, Carlos. "Error estimates for moving least square approximations." Bulletin of the Brazilian Mathematical Society 34, no. 2 (2003): 231–49. http://dx.doi.org/10.1007/s00574-003-0010-7.

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Octavia, Ranti Wilda Nur, and Umi Chotijah. "Implementasi Metode Least Square Untuk Prediksi Penjualan Kue Donat dan Bomboloni." Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi 11, no. 1 (2022): 251. http://dx.doi.org/10.35889/jutisi.v11i1.802.

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<p><strong>Abstrak.</strong> Prediksi Jumlah permintaan kue donat dan bomboloni oleh pelanggan (konsumen) Toko <em>Milly Donuts</em> selama ini tidak akurat, dimana jumlah produksi tidak sesuai dengan jumlah permintaan konsumen. Penelitian ini bertujuan mengimplementasikan Metode <em>Least Square</em> untuk melakukan <em>forecast</em> (prediksi) dalam penjualan. Metode <em>Least Square</em> merupakan salah satu teknik dalam menyusun <em>forecast</em> penjualan dengan meminimumkan fungsi kriteria jumlah kuadrat kesala
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Su, Moting, Zongyi Zhang, Ye Zhu, and Donglan Zha. "Data-Driven Natural Gas Spot Price Forecasting with Least Squares Regression Boosting Algorithm." Energies 12, no. 6 (2019): 1094. http://dx.doi.org/10.3390/en12061094.

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Natural gas is often described as the cleanest fossil fuel. The consumption of natural gas is increasing rapidly. Accurate prediction of natural gas spot prices would significantly benefit energy management, economic development, and environmental conservation. In this study, the least squares regression boosting (LSBoost) algorithm was used for forecasting natural gas spot prices. LSBoost can fit regression ensembles well by minimizing the mean squared error. Henry Hub natural gas spot prices were investigated, and a wide range of time series from January 2001 to December 2017 was selected. T
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Li, Long, and Jiacai Huang. "Recursive of Least Square Based Online Calibration Method in Geomagnetic Detection." MATEC Web of Conferences 232 (2018): 04087. http://dx.doi.org/10.1051/matecconf/201823204087.

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With the problem of attitude measurement accuracy is susceptible to various errors of geomagnetic survey, this paper establishes geomagnetic measurement error ellipsoid model by analysis of on the environment and own errors, uses the maximum likelihood algorithm for solving the static error correction coefficient. The experimental results show that, the maximum of attitude angle errors is less than 5° near blind direction, online combination correction can ensure the accuracy of attitude detection system under different shooting conditions.
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Seweh, Emmanuel Amomba, Zou Xiaobo, Feng Tao, Shi Jiachen, Haroon Elrasheid Tahir, and Muhammad Arslan. "Multivariate analysis of three chemometric algorithms on rapid prediction of some important quality parameters of crude shea butter using Fourier transform-near infrared spectroscopy." Journal of Near Infrared Spectroscopy 27, no. 3 (2019): 220–31. http://dx.doi.org/10.1177/0967033519830061.

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A comparative study of three chemometric algorithms combined with NIR spectroscopy with the aim of determining the best performing algorithm for quantitative prediction of iodine value, saponification value, free fatty acids content, and peroxide values of unrefined shea butter. Multivariate calibrations were developed for each parameter using supervised partial least squares, interval partial least squares, and genetic-algorithm partial least square regression methods to establish a linear relationship between standard reference and the Fourier transformed-near infrared predicted. Results sho
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Harshavardhan, P., and A. Raja. "Comparison on BER Performance Using Linear Filtering Least Square Method and Least Square Method for MIMO-OFDM Based Communication Systems." ECS Transactions 107, no. 1 (2022): 14197–204. http://dx.doi.org/10.1149/10701.14197ecst.

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In Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems, the Bit Error Rate is poor by using Linear Filtering Least Square method (LFLS) and Least Square (LS) method for massive MIMO-OFDM systems to extend the strength of the signal and to scale back the noise. Therefore the objective of the project is to maintain better Bit Error Rate performance. Materials and methods: Using Linear Filtering Least Square method, different values are used to enhance the Bit Error Rate (BER). The proposed method is compared with the least square method, the results are
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Koh, Show-Long Patrick. "WEIGHTED LEAST-SQUARE ESIMATE FOR SOFTWARE ERROR INTENSITY." Journal of the Chinese Institute of Industrial Engineers 25, no. 2 (2008): 162–73. http://dx.doi.org/10.1080/10170660809509081.

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Qi Cheng and Yingbo Hua. "Detection of cisoids using least square error function." IEEE Transactions on Signal Processing 45, no. 6 (1997): 1584–90. http://dx.doi.org/10.1109/78.600000.

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Dissertations / Theses on the topic "Least Square Error"

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Degtyarena, Anna Semenovna. "The window least mean square error algorithm." CSUSB ScholarWorks, 2003. https://scholarworks.lib.csusb.edu/etd-project/2385.

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In order to improve the performance of LMS (least mean square) algorithm by decreasing the amount of calculations this research proposes to make an update on each step only for those elements from the input data set, that fall within a small window W near the separating hyperplane surface. This work aims to describe in detail the results that can be achieved by using the proposed LMS with window learning algorithm in information systems that employ the methodology of neural network for the purposes of classification.
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Chen, Jiaxiong. "Power System State Estimation Using Phasor Measurement Units." UKnowledge, 2013. http://uknowledge.uky.edu/ece_etds/35.

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State estimation is widely used as a tool to evaluate the real time power system prevailing conditions. State estimation algorithms could suffer divergence under stressed system conditions. This dissertation first investigates impacts of variations of load levels and topology errors on the convergence property of the commonly used weighted least square (WLS) state estimator. The influence of topology errors on the condition number of the gain matrix in the state estimator is also analyzed. The minimum singular value of gain matrix is proposed to measure the distance between the operating point
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Savaux, Vincent. "Contribution to multipath channel estimation in an OFDM modulation context." Phd thesis, Supélec, 2013. http://tel.archives-ouvertes.fr/tel-00988283.

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In wireless communications systems, the transmission channel between the transmitter and the receiver antennas is one of the main sources of disruption for the signal. The multicarrier modulations, such as the orthogonal frequency division multiplexing (OFDM), are very robust against the multipath effect, and allow to recover the transmitted signal with a low error rate, when they are combined with a channel encoding. The channel estimation then plays a key role in the performance of the communications systems. In this PhD thesis, we study techniques based on least square (LS) and minimum mean
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Behrle, Charles D. "Computer simulation studies of multiple broadband target localization via frequency domain beamforming for planar arrays." Thesis, Monterey, California. Naval Postgraduate School, 1988. http://hdl.handle.net/10945/22976.

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Approved for public release; distribution is unlimited<br>Computer simulation studies of a frequency domain adaptive beamforming algorithm are presented. These simulation studies were conducted to determine the multiple broadband target localization capability and the full angular coverage capability of the algorithm. The algorithm was evaluated at several signal-to-noise ratios with varying sampling rates. The number of iterations that the adaptive algorithm took to reach a minimum estimation error was determined. Results of the simulation studies indicate that the algorithm can localize mult
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Feng, Dehua. "Determining Intersection Turning Movements with Detection Errors." University of Akron / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=akron1512746695445707.

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Yapici, Yavuz. "A Bidirectional Lms Algorithm For Estimation Of Fast Time-varying Channels." Phd thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613220/index.pdf.

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Effort to estimate unknown time-varying channels as a part of high-speed mobile communication systems is of interest especially for next-generation wireless systems. The high computational complexity of the optimal Wiener estimator usually makes its use impractical in fast time-varying channels. As a powerful candidate, the adaptive least mean squares (LMS) algorithm offers a computationally efficient solution with its simple first-order weight-vector update equation. However, the performance of the LMS algorithm deteriorates in time-varying channels as a result of the eigenvalue disparity, i.
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Thomas, Robin Rajan. "Optimisation of adaptive localisation techniques for cognitive radio." Diss., University of Pretoria, 2012. http://hdl.handle.net/2263/27076.

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Spectrum, environment and location awareness are key characteristics of cognitive radio (CR). Knowledge of a user’s location as well as the surrounding environment type may enhance various CR tasks, such as spectrum sensing, dynamic channel allocation and interference management. This dissertation deals with the optimisation of adaptive localisation techniques for CR. The first part entails the development and evaluation of an efficient bandwidth determination (BD) model, which is a key component of the cognitive positioning system. This bandwidth efficiency is achieved using the Cramer-Rao lo
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Avan, Muhammet. "Joint Frequency Offset And Channel Estimation." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/2/12610149/index.pdf.

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In this thesis study, joint frequency offset and channel estimation methods for single-input single-output (SISO) systems are examined. The performance of maximum likelihood estimate of the parameters are studied for different training sequences. Conventionally training sequences are designed solely for the channel estimation purpose. We present a numerical comparison of different training sequences for the joint estimation problem. The performance comparisons are made in terms of mean square estimation error (MSE) versus SNR and MSE versus the total training energy metrics. A novel estimation
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Glickman, Mark. "Disturbance monitoring in distributed power systems." Thesis, Queensland University of Technology, 2007. https://eprints.qut.edu.au/16497/1/Mark_Glickman_Thesis.pdf.

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Power system generators are interconnected in a distributed network to allow sharing of power. If one of the generators cannot meet the power demand, spare power is diverted from neighbouring generators. However, this approach also allows for propagation of electric disturbances. An oscillation arising from a disturbance at a given generator site will affect the normal operation of neighbouring generators and might cause them to fail. Hours of production time will be lost in the time it takes to restart the power plant. If the disturbance is detected early, appropriate control measures can be
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Glickman, Mark. "Disturbance monitoring in distributed power systems." Queensland University of Technology, 2007. http://eprints.qut.edu.au/16497/.

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Power system generators are interconnected in a distributed network to allow sharing of power. If one of the generators cannot meet the power demand, spare power is diverted from neighbouring generators. However, this approach also allows for propagation of electric disturbances. An oscillation arising from a disturbance at a given generator site will affect the normal operation of neighbouring generators and might cause them to fail. Hours of production time will be lost in the time it takes to restart the power plant. If the disturbance is detected early, appropriate control measures can be
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Books on the topic "Least Square Error"

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Gauss, Carl Friedrich. Theory of the combination of observations least subject to error: Part one, part two, supplement = Theoria combinationis observationum erroribus minimus obnoxiae : pars prior, pars posterior, supplementum. Society for Industrial and Applied Mathematics, 1995.

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van, Huffel Sabine, and International Workshop on Total Least Squares and Errors-in-Variables Modeling (2nd : 1996 : Leuven, Belgium), eds. Recent advances in total least squares techniques and errors-in-variables modeling. Society for Industrial and Applied Mathematics, 1997.

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Bevington, Philip R. Data reduction and error analysis for thephysical sciences. 2nd ed. McGraw-Hill, 1994.

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Van Huffel, Sabine, and Philippe Lemmerling, eds. Total Least Squares and Errors-in-Variables Modeling. Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-017-3552-0.

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D, Ghilani Charles, ed. Adjustment computations: Statistics and least squares in surveying and GIS. 3rd ed. John Wiley & Sons, 1997.

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Blais, J. A. R. Least-squares block adjustment of stereoscopic models and error analysis. University of Calgary, Division of Surveying Engineering, 1985.

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Rogers, Janet. Economic data: Handle with care. U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 1998.

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Center, Ames Research, ed. Round-off error propogation in four generally applicable, recursive, least-squares-estimation schemes. National Aeronautics and Space Administration, Ames Research Center, 1988.

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Huffel, Sabine. Total Least Squares and Errors-in-Variables Modeling: Analysis, Algorithms and Applications. Springer Netherlands, 2002.

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name, No. Total least squares and errors-in-variables modeling: Analysis, algorithms and applications. Kluwer Academic, 2001.

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Book chapters on the topic "Least Square Error"

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Principe, Jose C., Yadunandana N. Rao, and Deniz Erdogmus. "Error Whitening Wiener Filters: Theory and Algorithms." In Least-Mean-Square Adaptive Filters. John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471461288.ch10.

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Bekuma, Yohannes, Rituraj Jain, Balachandra Pattanaik, and Adugna Edosa. "Design of FIR Filter-Based on Least Square Error Method." In Algorithms for Intelligent Systems. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3311-0_35.

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Dam, H. H., Kok Lay Teo, Yanqun Liu, and S. Nordebo. "Optimum Pole Position for Digital Laguerre Network with Least Square Error Criterion." In Optimization Methods and Applications. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-3333-4_18.

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Li, Haoqi. "Generalized Least Square Estimation of Error-in-Variable Models and its Statistical Property." In Lecture Notes in Electrical Engineering. Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2386-6_200.

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Aduol, Francis W. O. "Robust Geodetic Parameter Estimation Under Least Squares Through Weighting on the Basis of the Mean Square Error." In Geodesy-The Challenge of the 3rd Millennium. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-05296-9_27.

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Smolik, Michal, Vaclav Skala, and Zuzana Majdisova. "A New Simple, Fast and Robust Total Least Square Error Computation in E2: Experimental Comparison." In Lecture Notes in Electrical Engineering. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14907-9_32.

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Awasthi, Neha, and Sukesha Sharma. "Comparative Analysis of Least Square, Minimum Mean Square Error and KALMAN Estimator Using DWT (Discrete Wavelet Transform)-Based MIMO-OFDM System." In Advances in Intelligent Systems and Computing. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8618-3_25.

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Ding, Qiangqiang, Shijie Guo, Geng Chen, and Shufeng Tang. "Thermal Error Modeling Method of Machining Center Linear Axis for Heat Conduction Mechanism." In Lecture Notes in Mechanical Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1876-4_99.

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AbstractTo address the thermal deformation of machine tool components, a thermal error prediction model based on the ROA-LSSVM network was proposed. First of all, the heat transfer mechanism of the linear feed system was analyzed. By analyzing temperature distribution characteristics during the heat transfer process, the best temperature measurement point position was determined to ensure that the thermal error could be accurately predicted. Secondly, in order to build a prediction model with high accuracy and strong robustness, Raccoon optimization algorithm (ROA) was proposed to optimize the
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Grabe, Michael. "Method of Least Squares." In Generalized Gaussian Error Calculus. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03305-6_8.

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Paige, Christopher C., and Zdeněk Strakoš. "Unifying Least Squares, Total Least Squares and Data Least Squares." In Total Least Squares and Errors-in-Variables Modeling. Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-017-3552-0_3.

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Conference papers on the topic "Least Square Error"

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Jiang, Yingjie, Du Tang, Ji Luo, Yu Chen, Bofang Zheng, and Yaojun Qiao. "Mitigation of Power Offset Induced by Hard-Decision-Error in Fiber Longitudinal Power Profile Estimation." In Optical Fiber Communication Conference. Optica Publishing Group, 2025. https://doi.org/10.1364/ofc.2025.w3e.6.

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We propose a fiber-nonlinearity distribution weighting-based scheme to mitigate the power offset induced by hard-decision (HD) error in least-square PPE. Experimental results demonstrate that the proposed method is as accurate as using transmitter-side (Tx) data.
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Xu, Huigang, and Liyan Zhang. "A channel estimation algorithm for train wireless communication system based on improved singular value decomposition linear least mean square error." In Fourth International Conference on Computer Vision and Pattern Analysis (ICCPA 2024), edited by Ji Zhao and Yonghui Yang. SPIE, 2024. http://dx.doi.org/10.1117/12.3038057.

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Skala, Vaclav. "Total Least Square Error Computation in E2." In CGI '16: Computer Graphics International. ACM, 2016. http://dx.doi.org/10.1145/2949035.2949036.

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Qi, Xiaoke, Yu Li, and Haining Huang. "A combined recursive least square and least mean square equalization scheme based on windowed error autocorrelation estimation." In 2013 6th International Congress on Image and Signal Processing (CISP). IEEE, 2013. http://dx.doi.org/10.1109/cisp.2013.6743905.

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Bolle, Ruud M., and Daniel Sabbah. "Differential Geometry Applied To Least-Square Error Surface Approximations." In OE LASE'87 and EO Imaging Symp (January 1987, Los Angeles), edited by Hua-Kuang Liu and Paul S. Schenker. SPIE, 1987. http://dx.doi.org/10.1117/12.939975.

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Yu, Chunxiao, Qin Shu, Yu Fan, Rui Mao, and Yi Zhou. "Recursive Deconvolution Algorithm Based on Least Mean Square Error." In 2023 8th International Conference on Communication, Image and Signal Processing (CCISP). IEEE, 2023. http://dx.doi.org/10.1109/ccisp59915.2023.10355838.

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Tausiesakul, Bamrung, and Nuria Gonzalez-Prelcic. "Power spectrum blind sampling using minimum mean square error and weighted least squares." In 2013 Asilomar Conference on Signals, Systems and Computers. IEEE, 2013. http://dx.doi.org/10.1109/acssc.2013.6810249.

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Borovytsky, Volodymyr N., and Valery V. Fesenko. "Imaging system performance evaluation: NETD, least-square error, or correlation." In AeroSense 2000, edited by Gary W. Kamerman, Upendra N. Singh, Christian Werner, and Vasyl V. Molebny. SPIE, 2000. http://dx.doi.org/10.1117/12.397818.

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Wei Wei, J. H. Mikkelsen, and O. K. Jensen. "Deembedding static nonlinearities of power amplifiers using least square error algorithm." In 2012 NORCHIP. IEEE, 2012. http://dx.doi.org/10.1109/norchp.2012.6403125.

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Pei, Soo-Chang, and Pai-Wei Wang. "New discrete inverse S transform with least square error in filtering." In ICASSP 2009 - 2009 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2009. http://dx.doi.org/10.1109/icassp.2009.4960252.

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Reports on the topic "Least Square Error"

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Hall, P., and J. S. Marron. Extent to which Least-Squares Cross-Validation Minimises Integrated Square Error in Nonparametric Density Estimation. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada153789.

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สิริภัทราวรรณ, อุบลรัตน์, та สุวัสสา พงษ์อำไพ. การประเมินอายุการเก็บแบบรวดเร็วของผลิตภัณฑ์อาหารแปรรูปโดยใช้ NIR specytoscopy และ Chemometrics : รายงานการวิจัย. จุฬาลงกรณ์มหาวิทยาลัย, 2014. https://doi.org/10.58837/chula.res.2014.58.

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งานวิจัยนี้พัฒนาการประเมินคุณภาพและอายุการเก็บของผลิตภัณฑ์อาหารแปรรูปพร้อมบริโภค ด้วยวิธี แบบรวดเร็วโดยใช้ NIR spectroscopy ร่วมกับ chemometrics ทำโดยเตรียมผลิตภัณฑ์ไส้กรอกหมูบรรจุใน ถุงพลาสติกภายใต้ภาวะสุญญากาศและเก็บรักษาที่อุณหภูมิ 4 °C ติดตามการเปลี่ยนแปลงคุณภาพทางเคมี (ค่า pH) ทางกายภาพ (ค่าแรงตัดขาด และ ค่าสี) ทางจุลินทรีย์ (จำนวนแบคทีเรียทั้ง หมด และ แบคทีเรียแลกติก) และทาง ประสาทสัมผัส (odor, color, appearance และ overall acceptability) ของผลิตภัณฑ์ในระหว่างการเก็บรักษา รวมทั้งวิเคราะห์โดยใช้ near infrared spectroscopy จากผลการทดลองพบว่า ผลิตภัณฑ์มีค่า pH ค่าแรงตัดขาด ค่าสี (L* (ความเข
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Carroll, Raymond J., P. Gallo, and L. J. Gleser. Comparisons of Least Squares and Errors-in-Variables Regression, with Special Reference to Randomized Analysis of Covariance. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada160967.

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HIGH PRECISION IDENTIFICATION METHOD OF MASS AND STIFFNESS MATRIX FOR SHEAR-TYPE FRAME TEST MODEL. The Hong Kong Institute of Steel Construction, 2023. http://dx.doi.org/10.18057/ijasc.2023.19.2.6.

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In the direct method of identifying the physical parameters of the shear-type frame structures through the frequencies and modes from the experimental modal analysis (EMA), the accuracy of the lumped mass depends on the initial mass, while the identified mass matrix and stiffness matrix are prone to generate some matrix elements without any physical meaning. In this paper, based on the natural frequencies and modes obtained from the EMA, an iterative constrained optimization solution for correcting mass matrix and a least squares solution for the lateral stiffness are proposed. The method take
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