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A Perspective of Conventional and Bio-inspired Optimization Techniques in Maximum Likelihood Parameter Estimation

Yongzhong Lu, Min Zhou, Shiping Chen, David Levy, Jicheng You
2018 Journal of Autonomous Intelligence  
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

Robert W. Santucci, Mahesh K. Banavar, Cihan Tepedelenlioglu, Andreas Spanias
2014 IEEE Transactions on Circuits and Systems Part 1: Regular Papers  
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

Gian Carlo Cardarilli, Alberto Nannarelli, Yann Oster, Massimo Petricca, Marco Re
2010 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers  
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  
., +, 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

Atiyeh Ghoreyshi, Henrietta Galiana
2011 Journal of Computational Neuroscience  
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

John Martin Ladrido, De La Salle University, Philippines
2019 International Journal of Emerging Trends in Engineering Research  
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

Timothy Sands
2019 Algorithms  
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]

Johan Schoukens, Lennart Ljung
2019 arXiv   pre-print
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  
-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  
., +, 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

Niels Rode Kristensen, Henrik Madsen, Sten Bay Jørgensen
2004 IFAC Proceedings Volumes  
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)  
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  
-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

Vincent Laurain, Roland Tóth, Dario Piga, Wei Xing Zheng
2015 Automatica  
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]

Hoon Lee, Tony Q. S. Quek, Sang Hyun Lee
2019 arXiv   pre-print
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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