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1. Full Text Bayesian Minimum Mean-Square Error Estimation for Classification Error-Part I: Definition and the Bayesian MMSE Error Estimator for Discrete Classification
by Dalton, L A and Dougherty, Edward R
IEEE transactions on signal processing, ISSN 1053-587X, 01/2011, Volume 59, Issue 1, pp. 115 - 129
error estimation | Bayesian estimation | Error analysis | Estimation | classification | Bayesian methods | minimum mean-square estimation | Tin | discrete histogram rule | genomics | Joints | Bioinformatics | small samples | Cancer | Engineering, Electrical & Electronic | Engineering | Technology | Science & Technology | Signal and communications theory | Miscellaneous | Telecommunications and information theory | Exact sciences and technology | Signal, noise | Signal processing | Applied sciences | Information, signal and communications theory | Signal representation. Spectral analysis | Detection, estimation, filtering, equalization, prediction | Bayesian statistical decision theory | Robust statistics | Usage | Analysis | Gaussian processes | Least squares | Innovations | Distribution (Probability theory) | Methods | Studies | Finite element analysis | Mean square errors | Classification | Errors | Statistical analysis | Mathematical analysis | Samples | Statistical methods | Bayesian analysis | Estimators
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2. Full Text Bayesian Minimum Mean-Square Error Estimation for Classification Error-Part II: Linear Classification of Gaussian Models
by Dalton, L A and Dougherty, E R
IEEE transactions on signal processing, ISSN 1053-587X, 01/2011, Volume 59, Issue 1, pp. 130 - 144
error estimation | Correlation | Bayesian estimation | Gaussian distribution | Closed-form solution | Covariance matrix | classification | Analytical models | Bayesian methods | linear classification | minimum-mean-square estimation | genomics | Robustness | small samples | Engineering, Electrical & Electronic | Engineering | Technology | Science & Technology | Signal processing | Applied sciences | Information, signal and communications theory | Miscellaneous | Telecommunications and information theory | Exact sciences and technology | Robust statistics | Bayesian statistical decision theory | Technology application | Usage | Analysis | Gaussian processes | Least squares | Innovations | Distribution (Probability theory) | Hessian matrices | Methods | Permissible error | Error analysis | Covariance | Mathematical analysis | Classification | Exact solutions | Mathematical models | Gaussian | Estimators
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3. Full Text Color demosaicking via directional linear minimum mean square-error estimation
by Lei Zhang and Xiaolin Wu
IEEE transactions on image processing, ISSN 1057-7149, 12/2005, Volume 14, Issue 12, pp. 2167 - 2178
linear minimum mean square-error estimation (LMMSE) | PSNR | Filtering | Color | Nonlinear filters | Bayer color filter array (CFA) | directional filtering | Image reconstruction | Visual perception | Image quality | Interpolation | Color demosaicking | Layout | Cameras | Directional filtering | Linear minimum mean square-error estimation (LMMSE) | Engineering, Electrical & Electronic | Engineering | Computer Science, Artificial Intelligence | Technology | Computer Science | Science & Technology | Signal and communications theory | Image processing | Telecommunications and information theory | Exact sciences and technology | Signal, noise | Signal processing | Applied sciences | Information, signal and communications theory | Detection, estimation, filtering, equalization, prediction | Colorimetry - methods | Data Interpretation, Statistical | Information Storage and Retrieval - methods | Artificial Intelligence | Image Interpretation, Computer-Assisted - methods | Linear Models | Computer Graphics | Algorithms | Numerical Analysis, Computer-Assisted | Least-Squares Analysis | Signal Processing, Computer-Assisted | Image Enhancement - methods | Analysis | Index Medicus
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4. Full Text Steady-State Mean-Square Error Analysis for Adaptive Filtering under the Maximum Correntropy Criterion
by Badong Chen and Lei Xing and Junli Liang and Nanning Zheng and Principe, Jose C
IEEE signal processing letters, ISSN 1070-9908, 07/2014, Volume 21, Issue 7, pp. 880 - 884
Noise | maximum correntropy criterion | Adaptive filters | Signal processing algorithms | Mean square error methods | Adaptive filtering | Educational institutions | Steady-state | Mathematical model | steady-state excess mean square error | Engineering, Electrical & Electronic | Engineering | Technology | Science & Technology | Error analysis | Approximation | Mathematical analysis | Exact solutions | Gaussian | Criteria
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5. Full Text Mutual information and minimum mean-square error in Gaussian channels
by Dongning Guo and Shamai, S and Verdu, S
IEEE transactions on information theory, ISSN 0018-9448, 04/2005, Volume 51, Issue 4, pp. 1261 - 1282
Additive noise | Smoothing methods | Filtering | Gaussian channel | optimal estimation | Wiener process | Statistics | minimum mean-square error (MMSE) | Power filters | Gaussian noise | nonlinear filtering | smoothing | Mutual information | Gaussian channels | Network address translation | Signal to noise ratio | Minimum mean-square error (MMSE) | Smoothing | Nonlinear filtering | Optimal estimation | Computer Science, Information Systems | Engineering, Electrical & Electronic | Engineering | Technology | Computer Science | Science & Technology | Applied sciences | Information, signal and communications theory | Telecommunications and information theory | Exact sciences and technology | Information theory | Random noise theory | Research | Mean square errors | Data smoothing | Communication channels | Information systems | Errors | Mathematical analysis | Scalars | Gaussian | Derivatives | Channels
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6. Full Text Minimum mean squares error beamforming with cyclic sub-vector optimisation
by Liu, Tuanning and Zhou, Yuanping and Ma, Yaoting and Miao, Rongzhen
IET signal processing, ISSN 1751-9675, 7/2020, Volume 14, Issue 5, pp. 300 - 306
Research Article | Engineering, Electrical & Electronic | Engineering | Technology | Science & Technology
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7. Full Text Minimal mean-square error for 3D MIMO beamforming weighting
by Xu, C and Cosmas, J and Zhang, Y
Electronics letters, ISSN 0013-5194, 11/2016, Volume 52, Issue 24, pp. 2019 - 2021
Wireless communications | beam areas | zero vector | minimal mean‐square error | 3D MIMO beamforming system | user terminals | beam direction determination | unit vector | radiofrequency interference | rectangular planar array | antenna arrays | horizontal array weight construction | weight determining method | signal‐to‐interference‐plus‐noise ratio | mean square error methods | MIMO communication | array signal processing | 5G system | 3D MIMO beamforming weighting | interference suppression | 5G mobile communication | mean‐square error minimisation | carrier frequency | undesired interference minimisation | planar antenna arrays | vectors | vertical array weight construction | array pattern vector | Engineering, Electrical & Electronic | Engineering | Technology | Science & Technology | Errors | Beams (radiation) | Beamforming | Mathematical analysis | Interference | Terminals | Vectors (mathematics) | Arrays
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8. Full Text Nonlocal linear minimum mean square error methods for denoising MRI
by Sudeep, P.V and Palanisamy, P and Kesavadas, Chandrasekharan and Rajan, Jeny
Biomedical signal processing and control, ISSN 1746-8094, 07/2015, Volume 20, pp. 125 - 134
Linear minimum mean square error | Rician distribution | Magnetic resonance image | Denoising | Discrete cosine transform | Principal component analysis | Engineering | Technology | Engineering, Biomedical | Science & Technology | Magnetic resonance imaging | Methods
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9. Full Text How to understand linear minimum mean-square-error transceiver design for multiple-input–multiple-output systems from quadratic matrix programming
by Xing, Chengwen and Li, Shuo and Fei, Zesong and Kuang, Jingming
IET communications, ISSN 1751-8628, 8/2013, Volume 7, Issue 12, pp. 1231 - 1242
quadratic matrix programming | MIMO system | iterative methods | least mean squares methods | unified LMMSE transceiver design framework | mathematical programming technology | multiple‐input‐multiple‐output systems | radio transceivers | unified linear minimum mean‐square‐error transceiver design framework | QMP problems | quadratic programming | matrix algebra | advanced wireless systems | MIMO communication | Engineering, Electrical & Electronic | Engineering | Technology | Science & Technology | Amplification | Design engineering | Relaying | Quadratic forms | Programming | Transceivers | Cognitive radio | Shot
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10. Full Text Mean-square error constrained approach to robust stochastic iterative learning control
by Li, Li and Liu, Yang and Yang, Zhile and Yang, Xiaofeng and Li, Kang
IET control theory & applications, ISSN 1751-8644, 1/2018, Volume 12, Issue 1, pp. 38 - 44
Research Article | iterative learning control | random noises | linear stochastic systems | Gaussian distribution | robust control | robust learning gain matrix | mean‐square error constrained approach | Kalman filtering‐based robust iterative learning control algorithm | mean‐square matrix | Kalman filters | mean square error methods | matrix algebra | Engineering, Electrical & Electronic | Engineering | Automation & Control Systems | Technology | Instruments & Instrumentation | Science & Technology
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11. Full Text Dimension reduction method of independent component analysis for process monitoring based on minimum mean square error
by Wang, Jingcheng and Zhang, Yanbin and Cao, Hui and Zhu, Wenzhi
Journal of process control, ISSN 0959-1524, 02/2012, Volume 22, Issue 2, pp. 477 - 487
Minimum mean square error | Process monitoring | Dimension reduction | Independent component analysis | Engineering | Automation & Control Systems | Engineering, Chemical | Technology | Science & Technology
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12. Full Text Assessing components of the model-based mean square error estimator for remote sensing assisted forest applications
by McRoberts, Ronald E and Næsset, Erik and Gobakken, Terje and Chirici, Gherardo and Condés, Sonia and Hou, Zhengyang and Saarela, Svetlana and Chen, Qi and Ståhl, Göran and Walters, Brian F
Canadian journal of forest research, ISSN 0045-5067, 2018, Volume 48, Issue 6, pp. 642 - 649
volume | corrélation spatiale | biomasse | séries de Taylor | biomass | Landsat | airborne laser scanning | Taylor series | spatial correlation | bootstrap | balayage laser aéroporté | méthode d’autoamorçage | Volume | Spatial correlation | Bootstrap | Biomass | Airborne laser scanning | Life Sciences & Biomedicine | Forestry | Science & Technology | Usage | Models | Mathematical models | Remote sensing | Methods | Forest dynamics | Forests | Parameter estimation | Mean square errors | Thresholds | Independent variables | Probabilistic inference | Variance | Satellite imagery | Satellites | Covariance | Dependent variables | Airborne lasers | Forest biomass | Error detection | Estimators | Landsat satellites
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13. Full Text Linear-minimum-mean-square-error observer for multi-rate sensor fusion with missing measurements
by Geng, Hang and Liang, Yan and Zhang, Xiaojing
IET control theory & applications, ISSN 1751-8644, 9/2014, Volume 8, Issue 14, pp. 1375 - 1383
estimation error system | optimal observer | sensor fusion | covariance | casuality constraint | multirate recursive computation | causality | H∞ filters | recursive estimation | multirate sensor fusion system | covariance analysis | linear‐minimum‐mean‐square‐error observer | equivalent noise | observer parameter | mean square error methods | observers | Engineering, Electrical & Electronic | Engineering | Automation & Control Systems | Technology | Instruments & Instrumentation | Science & Technology | Errors | Equivalence | Mathematical analysis | Observers | Mathematical models | Sensors | Recursive | Optimization
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