Log in

Relevant bibliographies by topics / ML estimation / Journal articles

To see the other types of publications on this topic, follow the link: ML estimation.

Journal articles on the topic 'ML estimation'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'ML estimation.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Goel, Dr Shalini. "AQI ML Estimation." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem48125.

Full text

Abstract:

Abstract— This study applies machine learning to predict the Air Quality Index (AQI) in Delhi, using data from 2015–2022 sourced from the Central Pollution Control Board. It considers key pollutants (PM2.5, PM10, NO₂, SO₂, CO, O₃) and meteorological factors. PM2.5 and vehicular emissions were identified as major AQI contributors. The findings support real-time AQI forecasting and align with UN SDGs 3 and 11, promoting public health and sustainable urban living through data-driven environmental strategies. Keywords— Air Quality Index, Machine Learning, Delhi Pollution, Predictive Modeling, Sust

APA, Harvard, Vancouver, ISO, and other styles

2

M., Alagurajan, and Vijayakumaran C. "ML Methods for Crop Yield Prediction and Estimation: An Exploration." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 3506–8. https://doi.org/10.35940/ijeat.C5775.029320.

Full text

Abstract:

Machine learning Has performed a essential position within the estimation of crop yield for both farmers and consumers of the products. Machine learning techniques learn from data set related to the environment on which the estimations and estimation are to be made and the outcome of the learning process are used by farmers for corrective measures for yield optimization. This paper we explore various ML techniques utilized in crop yield estimation and provide the detailed analysis of accuracy of the techniques.

APA, Harvard, Vancouver, ISO, and other styles

3

Williams, Brett, and Mal Boyle. "Estimation of External Blood Loss by Paramedics: Is There Any Point?" Prehospital and Disaster Medicine 22, no. 6 (2007): 502–6. http://dx.doi.org/10.1017/s1049023x0000532x.

Full text

Abstract:

AbstractObjectives:There are many patient assessment challenges in the prehospital setting, especially the estimation of external blood loss. Previous studies of experienced paramedics have demonstrated that external blood loss estimation is highly inaccurate. The objective of this study was to determine if undergraduate paramedic students could accurately estimate external blood loss on four surfaces commonly found in the prehospital environment.Methods:This prospective, observational, blinded study used a convenience sample of undergraduate students studying at Monash University during 2006.

APA, Harvard, Vancouver, ISO, and other styles

4

Samar, Mahvish, Xinzhong Zhu, and Huiying Xu. "Conditioning Theory for ML-Weighted Pseudoinverse and ML-Weighted Least Squares Problem." Axioms 13, no. 6 (2024): 345. http://dx.doi.org/10.3390/axioms13060345.

Full text

Abstract:

The conditioning theory of the ML-weighted least squares and ML-weighted pseudoinverse problems is explored in this article. We begin by introducing three types of condition numbers for the ML-weighted pseudoinverse problem: normwise, mixed, and componentwise, along with their explicit expressions. Utilizing the derivative of the ML-weighted pseudoinverse problem, we then provide explicit condition number expressions for the solution of the ML-weighted least squares problem. To ensure reliable estimation of these condition numbers, we employ the small-sample statistical condition estimation me

APA, Harvard, Vancouver, ISO, and other styles

5

Stoica, Petre, and Tomas Sundin. "Exact ML Estimation of Spectroscopic Parameters." Journal of Magnetic Resonance 145, no. 1 (2000): 108–14. http://dx.doi.org/10.1006/jmre.2000.2077.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Zheng, Yu, Lutao Liu, and Xudong Yang. "SPICE-ML Algorithm for Direction-of-Arrival Estimation." Sensors 20, no. 1 (2019): 119. http://dx.doi.org/10.3390/s20010119.

Full text

Abstract:

Sparse iterative covariance-based estimation, an iterative direction-of-arrival approach based on covariance fitting criterion, can simultaneously estimate the angle and power of incident signal. However, the signal power estimated by sparse iterative covariance-based estimation approach is inaccurate, and the estimation performance is limited to direction grid. To solve the problem above, an algorithm combing the sparse iterative covariance-based estimation approach and maximum likelihood estimation is proposed. The signal power estimated by sparse iterative covariance-based estimation approa

APA, Harvard, Vancouver, ISO, and other styles

7

Woltmann, Lucas, Claudio Hartmann, Dirk Habich, and Wolfgang Lehner. "Aggregate-based Training Phase for ML-based Cardinality Estimation." Datenbank-Spektrum 22, no. 1 (2022): 45–57. http://dx.doi.org/10.1007/s13222-021-00400-z.

Full text

Abstract:

AbstractCardinality estimation is a fundamental task in database query processing and optimization. As shown in recent papers, machine learning (ML)-based approaches may deliver more accurate cardinality estimations than traditional approaches. However, a lot of training queries have to be executed during the model training phase to learn a data-dependent ML model making it very time-consuming. Many of those training or example queries use the same base data, have the same query structure, and only differ in their selective predicates. To speed up the model training phase, our core idea is to

APA, Harvard, Vancouver, ISO, and other styles

8

Zulkifli, Raudhah, Nazim Aimran, Sayang Mohd Deni, and Fatin Najihah Badarisam. "A comparative study on the performance of maximum likelihood, generalized least square, scale-free least square, partial least square and consistent partial least square estimators in structural equation modeling." International Journal of Data and Network Science 6, no. 2 (2022): 391–400. http://dx.doi.org/10.5267/j.ijdns.2021.12.015.

Full text

Abstract:

Structural equation modeling offers various estimation methods for estimating parameters. The most used method in covariance-based structural equation modeling (CB-SEM) is the maximum likelihood (ML) estimator. The ML estimator is typically used when fitting models with normally distributed data. The growth of partial least squares path modeling (PLS-PM), including consistent partial least squares (PLSc), has also been noticed by researchers in the SEM fields. The PLSc has elevated interest in the scholastic setting in measuring the performance of various estimation methods in structural equat

APA, Harvard, Vancouver, ISO, and other styles

9

Liu, Yu-Sun, Shingchern You, and Yu-Chun Lai. "Machine Learning-Based Channel Estimation Techniques for ATSC 3.0." Information 15, no. 6 (2024): 350. http://dx.doi.org/10.3390/info15060350.

Full text

Abstract:

Channel estimation accuracy significantly affects the performance of orthogonal frequency-division multiplexing (OFDM) systems. In the literature, there are quite a few channel estimation methods. However, the performances of these methods deteriorate considerably when the wireless channels suffer from nonlinear distortions and interferences. Machine learning (ML) shows great potential for solving nonparametric problems. This paper proposes ML-based channel estimation methods for systems with comb-type pilot patterns and random pilot symbols, such as ATSC 3.0. We compare their performances wit

APA, Harvard, Vancouver, ISO, and other styles

10

Bashir, Rab Nawaz. "Internet of Things (IoT) and Machine Learning (ML) Assisted Reference Evapotranspiration (ETO) Estimations." Quaid-e-Awam University Research Journal of Engineering, Science & Technology 19, no. 2 (2021): 80–90. http://dx.doi.org/10.52584/qrj.1902.13.

Full text

Abstract:

Reference Evapotranspiration (ETo) is the amount of irrigation water required by a model crop to grow at its optimal level. ETo determination is a complex process that requires complicated calculations with many variables involved. There is a need to determine the ETo from available environmental conditions. Internet of Things (IoT) and Machine Learning (ML) based ETo estimation is proposed. IoT-assisted directly captured temperature data from the crop field is used to estimate the ETo. The estimated ETo can be used in many Precisions Agriculture (PA) applications especially in Precision Irrig

APA, Harvard, Vancouver, ISO, and other styles

11

Idowu, Janet Iyabo, Akin Soga Fasoranbaku, and Kayode Ayinde. "A New Modified Liu Ridge-Type Estimator for the Gamma Regression Model." International Journal of Research and Scientific Innovation X, no. XII (2024): 801–15. http://dx.doi.org/10.51244/ijrsi.2023.1012062.

Full text

Abstract:

The Gamma Regression Model (GRM) is a special form of the generalized linear model (GLM), where the response variable is positively skewed and well fitted to the gamma distribution. The most popular technique for estimating GRM coefficients is maximum likelihood (ML) estimation. The ML estimation method performs better if there is no correlation between the explanatory variables. It is known that the variance of the maximum likelihood estimator of the gamma regression coefficients is impacted in situations when the explanatory variables are correlated. Based on Aslam and Ahmad’s Modified Liu-R

APA, Harvard, Vancouver, ISO, and other styles

12

Atalay, Fırat. "Effect of Domaining in Mineral Resource Estimation with Machine Learning." Minerals 15, no. 4 (2025): 330. https://doi.org/10.3390/min15040330.

Full text

Abstract:

Machine learning (ML) is increasingly applied in earth sciences, including in mineral resource estimation. A critical step in this process is domaining, which significantly impacts estimation quality. However, the importance of domaining within ML-based resource estimation remains under-researched. This study aims to directly assess the effect of domaining on ML estimation accuracy. A copper deposit with well-defined, hard-boundary, low- and high-grade domains was used as a case study. Extreme Gradient Boosting (XGBoost), Support Vector Regression (SVR), and ensemble learning were employed to

APA, Harvard, Vancouver, ISO, and other styles

13

Prasad Gundu, Ram, P. Pardhasaradhi, S. Koteswara Rao, and V. Gopi Tilak. "TOA-based source localization using ML estimation." International Journal of Engineering & Technology 7, no. 2.7 (2018): 742. http://dx.doi.org/10.14419/ijet.v7i2.7.10936.

Full text

Abstract:

This paper proposes the Time of arrival (TOA) measurement model for finding the position of a stationary emitting source for Line-of-Sight (LOS) scenario. Here Maximum Likelihood Estimation (MLE) is used as the positioning algorithm. For approximation of the roots of the solution, which directly corresponds to the source location, the optimization techniques used are Gauss-Newton, Gradient descent and Newton-Raphson methods. Two different cases are considered for investigation in this paper. The first case compares the three different optimization techniques in terms of convergence rate. In th

APA, Harvard, Vancouver, ISO, and other styles

14

Monti Guarnieri, Andrea, and Stefano Tebaldini. "ML-Based Fringe-Frequency Estimation for InSAR." IEEE Geoscience and Remote Sensing Letters 7, no. 1 (2010): 136–40. http://dx.doi.org/10.1109/lgrs.2009.2028661.

Full text

APA, Harvard, Vancouver, ISO, and other styles

15

Chung, Pei-Jung, Mats Viberg, and Christoph F. Mecklenbräuker. "Broadband ML estimation under model order uncertainty." Signal Processing 90, no. 5 (2010): 1350–56. http://dx.doi.org/10.1016/j.sigpro.2009.11.013.

Full text

APA, Harvard, Vancouver, ISO, and other styles

16

Baby, Prathap Moothamadathil, Pramod Kumar, Rajesh Kumar, et al. "A novel method for blood volume estimation using trivalent chromium in rabbit models." Indian Journal of Plastic Surgery 47, no. 02 (2014): 242–48. http://dx.doi.org/10.4103/0970-0358.138961.

Full text

Abstract:

ABSTRACT Background: Blood volume measurement though important in management of critically ill-patients is not routinely estimated in clinical practice owing to labour intensive, intricate and time consuming nature of existing methods. Aims: The aim was to compare blood volume estimations using trivalent chromium [51 Cr(III)] and standard Evans blue dye (EBD) method in New Zealand white rabbit models and establish correction-factor (CF). Materials and Methods: Blood volume estimation in 33 rabbits was carried out using EBD method and concentration determined using spectrophotometric assay foll

APA, Harvard, Vancouver, ISO, and other styles

17

Chen, Yang, Chengcheng Hong, Michael R. Pinsky, Ting Ma, and Gilles Clermont. "Estimating Surgical Blood Loss Volume Using Continuously Monitored Vital Signs." Sensors 20, no. 22 (2020): 6558. http://dx.doi.org/10.3390/s20226558.

Full text

Abstract:

Background: There are currently no effective and accurate blood loss volume (BLV) estimation methods that can be implemented in operating rooms. To improve the accuracy and reliability of BLV estimation and facilitate clinical implementation, we propose a novel estimation method using continuously monitored photoplethysmography (PPG) and invasive arterial blood pressure (ABP). Methods: Forty anesthetized York Pigs (31.82 ± 3.52 kg) underwent a controlled hemorrhage at 20 mL/min until shock development was included. Machine-learning-based BLV estimation models were proposed and tested on normal

APA, Harvard, Vancouver, ISO, and other styles

18

Peng, Xing, Xinwu Li, Changcheng Wang, Haiqiang Fu, and Yanan Du. "A Maximum Likelihood Based Nonparametric Iterative Adaptive Method of Synthetic Aperture Radar Tomography and Its Application for Estimating Underlying Topography and Forest Height." Sensors 18, no. 8 (2018): 2459. http://dx.doi.org/10.3390/s18082459.

Full text

Abstract:

Synthetic aperture radar tomography (TomoSAR) is an important way of obtaining underlying topography and forest height for long-wavelength datasets such as L-band and P-band radar. It is usual to apply nonparametric spectral estimation methods with a large number of snapshots over forest areas. The nonparametric iterative adaptive approach for amplitude and phase estimation (IAA-APES) can obtain a high resolution; however, it only tends to work well with a small number of snapshots. To overcome this problem, this paper proposes the nonparametric iterative adaptive approach based on maximum lik

APA, Harvard, Vancouver, ISO, and other styles

19

Kim, Su-Young, David Huh, Zhengyang Zhou, and Eun-Young Mun. "A comparison of Bayesian to maximum likelihood estimation for latent growth models in the presence of a binary outcome." International Journal of Behavioral Development 44, no. 5 (2020): 447–57. http://dx.doi.org/10.1177/0165025419894730.

Full text

Abstract:

Latent growth models (LGMs) are an application of structural equation modeling and frequently used in developmental and clinical research to analyze change over time in longitudinal outcomes. Maximum likelihood (ML), the most common approach for estimating LGMs, can fail to converge or may produce biased estimates in complex LGMs especially in studies with modest samples. Bayesian estimation is a logical alternative to ML for LGMs, but there is a lack of research providing guidance on when Bayesian estimation may be preferable to ML or vice versa. This study compared the performance of Bayesia

APA, Harvard, Vancouver, ISO, and other styles

20

Hassan, Nuran M., M. Nagy, and Subhankar Dutta. "Statistical inference for the bathtub-shaped distribution using balanced and unbalanced sampling techniques." AIMS Mathematics 9, no. 9 (2024): 25049–69. http://dx.doi.org/10.3934/math.20241221.

Full text

Abstract:

<p>In order to reduce errors and enhance precision while estimating the unknown parameters of the distributions, it is crucial to choose a representative sample. The common estimation methods that estimate the parameters associated with the bathtub-shaped distribution include maximum likelihood (ML), maximum product of spacings estimation (MPSE), and Cramér-von Mises estimation (CME) methods. However, four modifications are used with the sample selection technique. They are simple random sampling (SRS), ranked set sampling (RSS), maximum ranked set sampling (MaxRSS), and double ranked se

APA, Harvard, Vancouver, ISO, and other styles

21

Bernardelli, Michał, and Barbara Kowalczyk. "Optimal Allocation of the Sample in the Poisson Item Count Technique." Acta Universitatis Lodziensis. Folia Oeconomica 3, no. 335 (2018): 35–47. http://dx.doi.org/10.18778/0208-6018.335.03.

Full text

Abstract:

Indirect methods of questioning are of utmost importance when dealing with sensitive questions. This paper refers to the new indirect method introduced by Tian et al. (2014) and examines the optimal allocation of the sample to control and treatment groups. If determining the optimal allocation is based on the variance formula for the method of moments (difference in means) estimator of the sensitive proportion, the solution is quite straightforward and was given in Tian et al. (2014). However, maximum likelihood (ML) estimation is known from much better properties, therefore determining the op

APA, Harvard, Vancouver, ISO, and other styles

22

Chen, Zhulin, Kun Jia, Chenchao Xiao, et al. "Leaf Area Index Estimation Algorithm for GF-5 Hyperspectral Data Based on Different Feature Selection and Machine Learning Methods." Remote Sensing 12, no. 13 (2020): 2110. http://dx.doi.org/10.3390/rs12132110.

Full text

Abstract:

Leaf area index (LAI) is an essential vegetation parameter that represents the light energy utilization and vegetation canopy structure. As the only in-operation hyperspectral satellite launched by China, GF-5 is potentially useful for accurate LAI estimation. However, there is no research focus on evaluating GF-5 data for LAI estimation. Hyperspectral remote sensing data contains abundant information about the reflective characteristics of vegetation canopies, but these abound data also easily result in a dimensionality curse. Therefore, feature selection (FS) is necessary to reduce data redu

APA, Harvard, Vancouver, ISO, and other styles

23

Nguyen, Hien D., Geoffrey J. McLachlan, Pierre Orban, Pierre Bellec, and Andrew L. Janke. "Maximum Pseudolikelihood Estimation for Model-Based Clustering of Time Series Data." Neural Computation 29, no. 4 (2017): 990–1020. http://dx.doi.org/10.1162/neco_a_00938.

Full text

Abstract:

Mixture of autoregressions (MoAR) models provide a model-based approach to the clustering of time series data. The maximum likelihood (ML) estimation of MoAR models requires evaluating products of large numbers of densities of normal random variables. In practical scenarios, these products converge to zero as the length of the time series increases, and thus the ML estimation of MoAR models becomes infeasible without the use of numerical tricks. We propose a maximum pseudolikelihood (MPL) estimation approach as an alternative to the use of numerical tricks. The MPL estimator is proved to be co

APA, Harvard, Vancouver, ISO, and other styles

24

Lee, Hyun Woo, and Sang Won Choi. "A Light-Weighted Machine Learning Approach to Channel Estimation for New-Radio Systems." Electronics 12, no. 23 (2023): 4740. http://dx.doi.org/10.3390/electronics12234740.

Full text

Abstract:

In this paper, we provide a light-weighted Machine Learning (ML) approach to channel estimation for New-Radio (NR) systems. Specifically, based on the equivalence between the Channel Impulse Response (CIR) in the time domain and its corresponding Channel Frequency Response (CFR) in the frequency domain, the light-weighted ML model for the channel estimation is shown to be established in comparison to the existing ML-based channel estimator. Furthermore, for practical use, the quantized weights for the light-weighted ML-based estimator are shown to be feasible without significant performance de

APA, Harvard, Vancouver, ISO, and other styles

25

CHEN, Haihua, and Masakiyo SUZUKI. "Exact Formulation for Stochastic ML Estimation of DOA." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E93-A, no. 11 (2010): 2141–52. http://dx.doi.org/10.1587/transfun.e93.a.2141.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Morelli, M., A. N. D'Andrea, and U. Mengali. "Feedforward ML-based timing estimation with PSK signals." IEEE Communications Letters 1, no. 3 (1997): 80–82. http://dx.doi.org/10.1109/4234.585803.

Full text

APA, Harvard, Vancouver, ISO, and other styles

27

Stein, S. "Differential delay/Doppler ML estimation with unknown signals." IEEE Transactions on Signal Processing 41, no. 8 (1993): 2717–19. http://dx.doi.org/10.1109/78.229901.

Full text

APA, Harvard, Vancouver, ISO, and other styles

28

Zoltowski, M. D., and T. S. Lee. "Beamspace ML bearing estimation incorporating low-angle geometry." IEEE Transactions on Aerospace and Electronic Systems 27, no. 3 (1991): 441–58. http://dx.doi.org/10.1109/7.81426.

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

Wasserman, Gary S. "EASY ML ESTIMATION OF NORMAL AND WEIBULL METRICS." Quality Engineering 12, no. 4 (2000): 569–81. http://dx.doi.org/10.1080/08982110008962622.

Full text

APA, Harvard, Vancouver, ISO, and other styles

30

Yunfei Chen and N. C. Beaulieu. "CRLBs for NDA ML estimation of UWB channels." IEEE Communications Letters 9, no. 8 (2005): 709–11. http://dx.doi.org/10.1109/lcomm.2005.1496590.

Full text

APA, Harvard, Vancouver, ISO, and other styles

31

Sidiropoulos, N. D., A. Swami, and B. M. Sadler. "Quasi-ML period estimation from incomplete timing data." IEEE Transactions on Signal Processing 53, no. 2 (2005): 733–39. http://dx.doi.org/10.1109/tsp.2004.840761.

Full text

APA, Harvard, Vancouver, ISO, and other styles

32

Carbonelli, Cecilia, and Urbashi Mitra. "Clustered ML Channel Estimation for Ultra-Wideband Signals." IEEE Transactions on Wireless Communications 6, no. 7 (2007): 2412–16. http://dx.doi.org/10.1109/twc.2007.051006.

Full text

APA, Harvard, Vancouver, ISO, and other styles

33

Falong, Luo, Ji Hongbing, and Zhao Xiaopeng. "The ML bearing estimation by using neural networks." Journal of Electronics (China) 10, no. 1 (1993): 1–8. http://dx.doi.org/10.1007/bf02778755.

Full text

APA, Harvard, Vancouver, ISO, and other styles

34

Djurović, Igor. "Quasi ML algorithm for 2-D PPS estimation." Multidimensional Systems and Signal Processing 28, no. 2 (2015): 371–87. http://dx.doi.org/10.1007/s11045-015-0344-5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

Harvey, Lewis O. "Efficient estimation of sensory thresholds with ML-PEST." Spatial Vision 11, no. 1 (1997): 121–28. http://dx.doi.org/10.1163/156856897x00159.

Full text

APA, Harvard, Vancouver, ISO, and other styles

36

Baggenstoss, Paul M. "Recursive Decimation/Interpolation for ML Chirp Parameter Estimation." IEEE Transactions on Aerospace and Electronic Systems 50, no. 1 (2014): 445–55. http://dx.doi.org/10.1109/taes.2013.120677.

Full text

APA, Harvard, Vancouver, ISO, and other styles

37

Thafasal Ijyas, V. P., and S. M. Sameer. "Low complexity metaheuristics for joint ML estimation problems." Applied Mathematics and Computation 230 (March 2014): 342–58. http://dx.doi.org/10.1016/j.amc.2013.12.103.

Full text

APA, Harvard, Vancouver, ISO, and other styles

38

Rostgaard, M., N. K. Poulsen, M. Lauritsen, and O. Ravn. "ML Estimation in Delta Based State Space Models." IFAC Proceedings Volumes 27, no. 8 (1994): 1579–84. http://dx.doi.org/10.1016/s1474-6670(17)47936-5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Park, Soojin, and Gregory J. Palardy. "Sensitivity Evaluation of Methods for Estimating Complier Average Causal Mediation Effects to Assumptions." Journal of Educational and Behavioral Statistics 45, no. 4 (2020): 475–506. http://dx.doi.org/10.3102/1076998620908599.

Full text

Abstract:

Estimating the effects of randomized experiments and, by extension, their mediating mechanisms, is often complicated by treatment noncompliance. Two estimation methods for causal mediation in the presence of noncompliance have recently been proposed, the instrumental variable method (IV-mediate) and maximum likelihood method (ML-mediate). However, little research has examined their performance when certain assumptions are violated and under varying data conditions. This article addresses that gap in the research and compares the performance of the two methods. The results show that the distrib

APA, Harvard, Vancouver, ISO, and other styles

40

Kouider, Mohammed Ridha, Nesrine Idiou, Samia Toumi, and Fatah Benatia. "Maximum lq-likelihood estimator of the heavy-tailed distribution parameter." Croatian review of economic, business and social statistics 10, no. 2 (2024): 29–48. https://doi.org/10.62366/crebss.2024.2.003.

Full text

Abstract:

Studying the extreme value theory (EVT) involves multiple main objectives, among them the estimation of the tail index parameter. Some estimation methods are used to estimate the tail index parameter like maximum likelihood estimation (MLE). Additionally, the Hill estimator is one type of maximum likelihood estimator, which is a more robust with a large sample than a small sample. This research proposes the construction of an alternative estimator for the parameter of the heavy-tailed distribution using the maximum lq-likelihood estimation (MLqE) approach in order to adapt the ML and Hill esti

APA, Harvard, Vancouver, ISO, and other styles

41

Choi, Yang-Ho. "ML-based Direction Estimation for Noncircular Signals in Moving Array." Journal of the Institute of Electronics and Information Engineers 58, no. 7 (2021): 49–55. http://dx.doi.org/10.5573/ieie.2021.58.7.49.

Full text

APA, Harvard, Vancouver, ISO, and other styles

42

Ben, Guangli, Xifeng Zheng, Yongcheng Wang, Ning Zhang, and Xin Zhang. "A Local Search Maximum Likelihood Parameter Estimator of Chirp Signal." Applied Sciences 11, no. 2 (2021): 673. http://dx.doi.org/10.3390/app11020673.

Full text

Abstract:

A local search Maximum Likelihood (ML) parameter estimator for mono-component chirp signal in low Signal-to-Noise Ratio (SNR) conditions is proposed in this paper. The approach combines a deep learning denoising method with a two-step parameter estimator. The denoiser utilizes residual learning assisted Denoising Convolutional Neural Network (DnCNN) to recover the structured signal component, which is used to denoise the original observations. Following the denoising step, we employ a coarse parameter estimator, which is based on the Time-Frequency (TF) distribution, to the denoised signal for

APA, Harvard, Vancouver, ISO, and other styles

43

Saravanakumar C and Usha Bhanu N. "Estimating R, L and C in Arithmetic Circuits using ML." International Research Journal of Multidisciplinary Scope 05, no. 02 (2024): 745–53. http://dx.doi.org/10.47857/irjms.2024.v05i02.0633.

Full text

Abstract:

In Very Large Scale Integration (VLSI) circuits, the estimation techniques for resistors (R), inductors (L), and capacitors (C) heavily rely on segmented circuit analysis, which involves usage of complex mathematical simplification models. These methods have been conventionally applied to estimate the behavior of circuits, but when faced with systems featuring unique circuit architectures, they often encounter inaccuracies and limitations. The significance of adders as fundamental building blocks in intricate circuit design cannot be overstated. In such complex circuits, various parameters, in

APA, Harvard, Vancouver, ISO, and other styles

44

Chen, Haihua, Shibao Li, Jianhang Liu, Yiqing Zhou, and Masakiyo Suzuki. "Efficient AM Algorithms for Stochastic ML Estimation of DOA." International Journal of Antennas and Propagation 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/4926496.

Full text

Abstract:

The estimation of direction-of-arrival (DOA) of signals is a basic and important problem in sensor array signal processing. To solve this problem, many algorithms have been proposed, among which the Stochastic Maximum Likelihood (SML) is one of the most concerned algorithms because of its high accuracy of DOA. However, the estimation of SML generally involves the multidimensional nonlinear optimization problem. As a result, its computational complexity is rather high. This paper addresses the issue of reducing computational complexity of SML estimation of DOA based on the Alternating Minimizat

APA, Harvard, Vancouver, ISO, and other styles

45

Pabbati, Omkar, and Rutvij Joshi. "Performance Analysis of ML-based Low Complex CFO Estimation for MIMO-OFDMA Uplink Systems." ECTI Transactions on Electrical Engineering, Electronics, and Communications 20, no. 3 (2022): 307–14. http://dx.doi.org/10.37936/ecti-eec.2022203.246952.

Full text

Abstract:

Carrier frequency offset (CFO) estimation in multiuser multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system is investigated in this study. MIMO-OFDM is very sensitive to CFOs due to oscillator frequency mismatch and/or Doppler shift. Inaccurate CFO estimation results in intercarrier interference (ICI) through the loss of orthogonality among subcarriers. In this paper, the performance of the ML and APFE algorithm is analyzed for CFO estimation. ML becomes extremely complex due to the multidimensional exhaustive search issue, which is the basic concern i

APA, Harvard, Vancouver, ISO, and other styles

46

Hassan, Diar, George A. Isaac, Peter A. Taylor, and Daniel Michelson. "Optimizing Radar-Based Rainfall Estimation Using Machine Learning Models." Remote Sensing 14, no. 20 (2022): 5188. http://dx.doi.org/10.3390/rs14205188.

Full text

Abstract:

Weather radar research has produced numerous radar-based rainfall estimators based on climate, rainfall intensity, a variety of ground-truthing instruments and sensors (e.g., rain gauges, disdrometers), and techniques. Although each research direction gives improvement, their collective application in an operational sense still yields uncertainty in rainfall estimation at times. This study aims to explore the concept of implementing Machine Learning (ML) models in optimizing the radar-based rainfall estimations at the bin level from a group of estimator. The Canadian King City C-Band radar was

APA, Harvard, Vancouver, ISO, and other styles

47

Bağcı Genel, Kübra. "A Comparison of Parameter Estimation Methods for the Inverted Modified Lindley Distribution." Journal of the Institute of Science and Technology 14, no. 3 (2024): 1388–96. http://dx.doi.org/10.21597/jist.1488247.

Full text

Abstract:

The Inverted Modified Lindley (IML) distribution has been shown to exhibit superior fitting capabilities compared to the exponential and Lindley distributions. This study investigates the parameter estimation of the IML distribution using the Least Squares (LS), Cramer von Misses (CvM), and Maximum Likelihood (ML) methods. A Monte Carlo simulation study is conducted to compare the efficiency of the ML, LS, and CvM methods in estimating the parameters of the IML distribution. Moreover, real data applications from various fields are provided using related estimation methods. The fitting performa

APA, Harvard, Vancouver, ISO, and other styles

48

Cao, Guocan, Xiang Xu, and Dacheng Xu. "Real-Time Calibration of Magnetometers Using the RLS/ML Algorithm." Sensors 20, no. 2 (2020): 535. http://dx.doi.org/10.3390/s20020535.

Full text

Abstract:

This study presents a new real-time calibration algorithm for three-axis magnetometers by combining the recursive least square (RLS) estimation and maximum likelihood (ML) estimation methods. Magnetometers are widely employed to determine the heading information by sensing the magnetic field of earth; however, they are vulnerable to ambient magnetic disturbances. This makes the calibration of a magnetometer inevitable before it is employed. In this paper, first, a complete measurement error model of the magnetometer is studied, and a simplified model is developed. Then, the real-time RLS algor

APA, Harvard, Vancouver, ISO, and other styles

49

Pouzo, Demian, Zacharias Psaradakis, and Martin Sola. "Maximum Likelihood Estimation in Markov Regime‐Switching Models With Covariate‐Dependent Transition Probabilities." Econometrica 90, no. 4 (2022): 1681–710. http://dx.doi.org/10.3982/ecta17249.

Full text

Abstract:

This paper considers maximum likelihood (ML) estimation in a large class of models with hidden Markov regimes. We investigate consistency of the ML estimator and local asymptotic normality for the models under general conditions, which allow for autoregressive dynamics in the observable process, Markov regime sequences with covariate‐dependent transition matrices, and possible model misspecification. A Monte Carlo study examines the finite‐sample properties of the ML estimator in correctly specified and misspecified models. An empirical application is also discussed.

APA, Harvard, Vancouver, ISO, and other styles

50

Islam, Md Didarul, Liping Di, Faisal Mueen Qamer, et al. "Rapid Rice Yield Estimation Using Integrated Remote Sensing and Meteorological Data and Machine Learning." Remote Sensing 15, no. 9 (2023): 2374. http://dx.doi.org/10.3390/rs15092374.

Full text

Abstract:

This study developed a rapid rice yield estimation workflow and customized yield prediction model by integrating remote sensing and meteorological data with machine learning (ML). Several issues need to be addressed while developing a crop yield estimation model, including data quality issues, data processing issues, selecting a suitable machine learning model that can learn from few available time-series data, and understanding the non-linear relationship between historical crop yield and remote sensing and meteorological factors. This study applied a series of data processing techniques and

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!