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A Perspective of Conventional and Bio-inspired Optimization Techniques in Maximum Likelihood Parameter Estimation
2018
Journal of Autonomous Intelligence
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It has been widely used in a good many multi-disciplines such as econometrics, data modelling in nuclear and particle physics, and geographical satellite image classification, and so forth. ...
key issues and encourage the researches for further progress. ...
Acknowledgments This work is partly supported by the Fundamental Research Funds for the Central Universities in China (HUST: 2016YXMS105). ...
doi:10.32629/jai.v1i2.28
fatcat:7hfsl4shkjbpvggyvydwgv2lle
Energy-Efficient Distributed Estimation by Utilizing a Nonlinear Amplifier
2014
IEEE Transactions on Circuits and Systems Part 1: Regular Papers
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This dissertation demonstrates that implementing distributed estimation using nonlinear sensors can boost system efficiency and is compatible with existing techniques from the literature for boosting efficiency ...
Secondly, the equations conventionally used for estimators and performance expectations in linear amplify-andforward systems fail. ...
The maximum path delay time, was swept between 0 to 15 sampling rate symbol times or 60 oversampled symbols. ...
doi:10.1109/tcsi.2013.2268354
fatcat:inv2xx6oubca7m6dwxkq777ssa
Design of large polyphase filters in the Quadratic Residue Number System
2010
2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers
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The maximum likelihood of the time-varying field is solved for using a single expectation maximization step after each received data snapshot. ...
We have recently developed algorithms for adaptive filters based on Volterra, Wiener and Hammerstein models. We have applied these algorithms to real applications with good results. ...
doi:10.1109/acssc.2010.5757589
fatcat:ccxnu5owr5fyrcjcqukumerueq
2015 Index IEEE Transactions on Automatic Control Vol. 60
2015
IEEE Transactions on Automatic Control
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., +, TAC March 2015 799-805
Expectation-maximization algorithms
Robust Partial-Learning in Linear Gaussian Systems. ...
., +, TAC Jan. 2015 240-245 Linear Quadratic Regulation and Stabilization of Discrete-Time Systems With Delay and Multiplicative Noise. ...
doi:10.1109/tac.2015.2512305
fatcat:5gut6qeomfh73fwfvehzujbr5q
Automatic classification and robust identification of vestibulo-ocular reflex responses: from theory to practice
2011
Journal of Computational Neuroscience
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Prediction errors were less than 1 deg for simulations and ranged from .69 deg to 2.1 deg for the clinical data. ...
We have developed GNL-HybELS (Generalized NonLinear Hybrid Extended Least Squares), an algorithmic tool to simultaneously classify and identify the responses of a multi-mode nonlinear system with delay ...
Interested users of this approach can contact us for a copy of the software soon to be released -IP right protection is currently underway.
Acknowledgements ...
doi:10.1007/s10827-010-0307-7
pmid:21249516
fatcat:fiuvw3g7nnhahfha4huzxhx5ie
Comparative Survey of Signal Processing and Artificial Intelligence Based Channel Equalization Techniques and Technologies
2019
International Journal of Emerging Trends in Engineering Research
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It was found that gaps such as complexity and convergence time are potential areas for extending the performance and limits of existing channel equalizers. ...
The authors begin with the theory behind channel equalization followed by techniques, and the technological realizations for achieving the proper filter in response to variations of the channel. ...
Acknowledgment De La Salle University is acknowledged for supporting this work. ...
doi:10.30534/ijeter/2019/14792019
fatcat:rz2vabommrhdrgw47zpino5vou
Comparison and Interpretation Methods for Predictive Control of Mechanics
2019
Algorithms
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These controllers are compared to each other with noise and modeling errors, and the many figures of merit are used: tracking error and rate error deviations and means, in addition to total mean cost. ...
Predictive controllers (both continuous and sampled-data) derived from the outset to be optimal by first solving an optimization problem with the governing dynamic equations of motion lead to several controllers ...
continuing associations with Stanford and Columbia Universities. ...
doi:10.3390/a12110232
fatcat:yi6uuzs74vfx5pikpsmh4r27pe
Nonlinear System Identification: A User-Oriented Roadmap
[article]
2019
arXiv
pre-print
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Firstly, nonlinear system identification is introduced to a wide audience, guiding practicing engineers and newcomers in the field to a sound solution of their data driven modeling problems for nonlinear ...
The reader will be referred to the existing literature for detailed mathematical explanations and formal proofs. ...
on the battery model in Figures 29 and 30 ; Erliang Zhang (Zhengzhou University) and Maarten Schoukens (Vrije Universiteit Brussel) for the results on process noise detection in Figure S24 ; Alireza ...
arXiv:1902.00683v1
fatcat:r6jwxklmyjdsfged6zflewsxki
2021 Index IEEE Transactions on Wireless Communications Vol. 20
2021
IEEE Transactions on Wireless Communications
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-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021. ...
Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. ...
., +, TWC Dec. 2021 8081-8095 Impulse noise Maximum Rate Scheduling With Adaptive Modulation in Mixed Impulsive Noise and Additive White Gaussian Noise Environments. ...
doi:10.1109/twc.2021.3135649
fatcat:bgd3vzb7pbee7jp75dnbucihmq
2014 Index IEEE Transactions on Neural Networks and Learning Systems Vol. 25
2014
IEEE Transactions on Neural Networks and Learning Systems
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., +, TNNLS Dec. 2014 2303-2308
Estimation theory
A Novel Estimation Algorithm Based on Data and Low-Order Models for
Virtual Unmodeled Dynamics. ...
., Adaptive Quasi-Newton Algorithm for Source Extraction via CCA Approach; TNNLS Apr. 2014 677-689 Zhang, Y., see
., A Novel Estimation Algorithm Based on Data and Low-Order Models for Virtual Unmodeled ...
The Field of Values of a Matrix and Neural Networks. Georgiou, G.M., TNNLS Sep. 2014 ...
doi:10.1109/tnnls.2015.2396731
fatcat:ztnfcozrejhhfdwg7t2f5xlype
Stochastic Grey-Box Modelling as a Tool for Improving the Quality of First Engineering Principles Models
2004
IFAC Proceedings Volumes
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Based on this model, the "missing" data points in the slow sampled measurements are estimated following the expectation maximization approach. ...
Abstract: In this paper, we provide a novel iterative identification algorithm for multi-rate sampled data systems. ...
J. and R. J. Tibshirani (1990 ...
doi:10.1016/s1474-6670(17)38722-0
fatcat:3n2uqgrghbd2xdp4tqoyvnvwgu
Welcome Messages
2019
2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)
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The database along with its source code will be made open source for the research and academic purpose. ...
The use of multiuser multipleinput multiple-output (MU-MIMO) systems, where multiple data can be sent to multiple users, is highly expected. ...
Each station first estimates the delay time for each AP, and then selects the AP being expected to provide the minimum delay time. ...
doi:10.1109/ispacs48206.2019.8986291
fatcat:gu4zaxsqkncp5n2ebj5fybk7ce
2020 Index IEEE Transactions on Systems, Man, and Cybernetics: Systems Vol. 50
2020
IEEE Transactions on Systems, Man & Cybernetics. Systems
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-that appeared in this periodical during 2020, and items from previous years that were commented upon or corrected in 2020. ...
Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. ...
., +, TSMC June 2020 2284-2292 Expectation-maximization algorithms Utility-Based Model for Characterizing the Evolution of Social Networks. ...
doi:10.1109/tsmc.2021.3054492
fatcat:zartzom6xvdpbbnkcw7xnsbeqy
An instrumental least squares support vector machine for nonlinear system identification
2015
Automatica
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modeling error. ...
via nonparametric estimation of the involved nonlinearities in a computationally and stochastically attractive way. ...
Let E be the expectation operator and for a random process f (x) with f : R ng → R, let m f (x) = E{f (x)} denote the mean function. ...
doi:10.1016/j.automatica.2015.02.017
fatcat:tesk6y25hfeijngki5m646tele
A Deep Learning Approach to Universal Binary Visible Light Communication Transceiver
[article]
2019
arXiv
pre-print
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We develop a new training algorithm that addresses the dimming constraints through a dual formulation of the optimization. ...
An unsupervised DL technique is employed for obtaining a neural network to replace the encoder-decoder pair that recovers the message from the optically transmitted signal. ...
The position of the LED is fixed at (1.5 m, 3 m) , while the PD suffering from the delayed ISI signal reflected by the wall is located at random on the floor as (0 m, P m) with P being the uniform random ...
arXiv:1910.12048v1
fatcat:prjbuvug4rdcpgus5xyigcskfa
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