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The Factorized Distribution Algorithm and the Minimum Relative Entropy Principle
[chapter]
2006
Studies in Computational Intelligence
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The relation between the Factorized Distribution Algorithm FDA and the MinRel approximation is shown. ...
In this paper the major design issues of EDA's are discussed using an interdisciplinary framework, the minimum relative entropy (MinRel) approximation. ...
We discuss the problem of computing approximations of distributions using factorizations is investigated with the framework of minimum relative entropy. ...
doi:10.1007/978-3-540-34954-9_2
fatcat:q36tru63wrd57erm6srh2m5cei
The Factorized Distribution Algorithm and the Minimum Relative Entropy Principle
unpublished
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The relation between the Factorized Distribution Algorithm FDA and the M inRel approximation is shown. ...
In this paper the major design issues of EDA's are discussed using an interdisciplinary framework, the minimum relative entropy (M inRel) approximation. ...
Thus MaxEnt is a special case of the minimum relative entropy M inRel principle. But there exists another justification of the MaxEnt solution, it is given by the Maximum Log-Likelihood principle. ...
fatcat:g3rmrrnxmnczlflfo7pkawuvjy
A Load Balancing Algorithm Based on Maximum Entropy Methods in Homogeneous Clusters
2014
Entropy
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By calculating the entropy of the system and using the maximum entropy principle to ensure that each scheduling and migration is performed following the increasing tendency of the entropy, the system can ...
The result of simulation experiments show that this algorithm is more advanced when it comes to the time and extent of the load balance of the homogeneous cluster system compared with traditional algorithms ...
Acknowledgments The authors thank the editor and referees for their helpful conmments. ...
doi:10.3390/e16115677
fatcat:faw4bgf23jgc5mgqmpqfc3dnaa
Time Delay Estimation via Minimum Entropy
2007
IEEE Signal Processing Letters
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However, with the generalization of the idea to non-Gaussian signals (e.g., speech), the joint entropy-based new TDE algorithm manifests a potential to outperform the MCCC-based method. ...
The approach is based on the multichannel crosscorrelation coefficient (MCCC) and was found more robust to noise and reverberation. ...
In this letter, the concept of minimum entropy is introduced, and a novel entropybased multichannel TDE algorithm is developed. ...
doi:10.1109/lsp.2006.884038
fatcat:p5ze4cibcrap5d2v6n6qewkzd4
Combining F-K Filter with Minimum Entropy Stolt Migration Algorithm for Subsurface Object Imaging and Background Permittivity Estimation
2011
Procedia Engineering
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Besides, a Stolt migration algorithm combined F-K filter with minimum entropy technique is proposed to improve the focus effect of the radar image and realize the precise inversion of background relative ...
Synthetic data generated by FDTD have been used to test the improved migration algorithm, and the results show that the presented algorithm can achieve comparative results produced by windowed filter based ...
Acknowledgement This work is supported by the NSFC (No.6106202009) and Key Technology R&D Program of Jiangxi (No. 2009BGB02200). ...
doi:10.1016/j.proeng.2011.11.2558
fatcat:4qjj23errnakra5fdxgo3ox62q
Applications of Entropy in Finance: A Review
2013
Entropy
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Although the concept of entropy is originated from thermodynamics, its concepts and relevant principles, especially the principles of maximum entropy and minimum cross-entropy, have been extensively applied ...
In this paper, we review the concepts and principles of entropy, as well as their applications in the field of finance, especially in portfolio selection and asset pricing. ...
Acknowledgments The authors would like to thank the editor and three anonymous referees for their valuable comments and suggestions. ...
doi:10.3390/e15114909
fatcat:ryraewbaxfa5jbvx6eubcazx6e
Robust Detection Method of Arrival Time Difference Under Minimum Maximum Entropy Criterion
2017
Journal Electrical and Electronic Engineering
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Under the minimum maximum entropy criterion, the adaptive filter weight vector will be convergence, and its peak position indicates the arrival time difference. ...
The computer simulation experiments show the estimation performance of this algorithm under different signal and noise ratio or different impulsive noise intension. ...
They gave her knowledge, progress, and higher hope in the different stages of life. ...
doi:10.11648/j.jeee.20170502.16
fatcat:fmlutkipijhedfxf5wil2rdqeq
The Evaluation of Effectiveness for the Collaborative Combat of an Unmanned Aerial Vehicle Based on Grey Minimum Entropy
2021
Journal of Aerospace Technology and Management
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At last, the principle of minimum relative entropy is adopted to obtain a more reasonable weight distribution coefficient. ...
The same study also applied the principle of minimum entropy analysis to obtain the objective weight, which takes into account the interaction between the indicators and greatly improves the objectivity ...
DATA AVAILABILITY STATEMENT All the datasets were generated during the current study. ...
doi:10.1590/jatm.v13.1222
fatcat:7wuxxvknzzhongeaocgkjgq7xe
Finding the Optimal Sample Based on Shannon's Entropy and Genetic Algorithms
[chapter]
2015
Lecture Notes in Computer Science
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In this paper we propose a statistical method based on Shannon's Conditional Entropy which uses a rugged genetic algorithm to find the optimal pdf. ...
The fitness of an individual is determined by Shannon´s entropy encoded in its genome and an additional constraint related to the "quality" of this solution. ...
The fitness of an individual is based on the minimum entropy principle and an additional constraint related to the "quality" of the solution. ...
doi:10.1007/978-3-319-27060-9_29
fatcat:3p7dksqwdvag5hadignzjeicba
Study on Ultra-short-time Power Forecast of Photovoltaic System based on Ground-based Cloud Image Recognition and Key Impact Factors
2020
E3S Web of Conferences
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Through verification and comparison analysis, it is concluded that the recognition accuracy of the hybrid entropy threshold method is higher, and the average relative error can be controlled at about 5% ...
Using the correlation analysis, among many impact factors with high correlation, five are extracted as input parameters of a BP network optimized by genetic algorithm (GA-BP). ...
After calculation, the average relative error of the whole day using the fixed threshold method is 10.77%, the maximum information entropy threshold method is 21.84%, and the minimum cross entropy threshold ...
doi:10.1051/e3sconf/202018502028
fatcat:ga7q3z6qrrdgviuk5j3kvavwye
Entropy-based Dispatching: Academic Insights and Perspectives through Bibliometric Analysis
2020
IET Collaborative Intelligent Manufacturing
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They compare and analyse the relationship between dispatching problems and entropy theory in different research fields, and provide detailed overviews and discussions on hot topics and potential research ...
Entropy-based dispatching has attracted more and more attention from professional scholars and engineers. The quantity and quality of publications related to this topic are increasing rapidly. ...
Acknowledgments The authors are grateful for the financial support partly from the Natural ...
doi:10.1049/iet-cim.2020.0011
fatcat:melcjv2y6jasfmvylmgiv5454u
Renormalization Analysis of Topic Models
2020
Entropy
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In this paper, the renormalization procedure is developed for the probabilistic Latent Semantic Analysis (pLSA), and the Latent Dirichlet Allocation model with variational Expectation–Maximization algorithm ...
A combination of renormalization procedure with the Renyi entropy approach allows for quick searching of the optimal number of topics. ...
Our calculations demonstrate that the fastest procedures are renormalization with the random merging of topics and with the minimum local entropy principle of merging. ...
doi:10.3390/e22050556
pmid:33286328
pmcid:PMC7517079
fatcat:kf3ucghnlzcgtdvco2coipnvoq
Max-Entropy Feed-Forward Clustering Neural Network
[article]
2015
arXiv
pre-print
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Entropy-Based Principle is the principle with which we could estimate the unknown distribution under some limited conditions. ...
If we take Entropy-Based Principle into consideration, the outputs for each sample could be represented as the distribution of this sample for different clusters. ...
When we estimate the unknown probability distribution for data manifold, the Max-Entropy Principle works well, and the clustering algorithm is designed based on this principle.
B. ...
arXiv:1506.03623v1
fatcat:62j5tchnofh45nbvpai3ztmxci
The Estimation of Distributions and the Minimum Relative Entropy Principle
2005
Evolutionary Computation
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FDA uses the ADF to compute an approximate factorization of the unknown distribution. The factors are marginal distributions, whose values are computed from samples. ...
All proposed algorithms try to minimize the Kullback-Leibler divergence ÃÄ between the unknown distribution Դܵ and a class մܵ of approximations. The Kullback-Leibler divergence is not symmetric. ...
We have identified two principles used for the approximation -minimum relative entropy and minimum expected log-likelihood ratio. Both principles are closely related. ...
doi:10.1162/1063656053583469
pmid:15901422
fatcat:6aq3mlpy2vf67l7pqeaulbm2y4
Laplace Entropy and its Application to Time Delay Estimation for Speech Signals
2007
2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07
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Since there is no rigorous mathematical formula for speech entropy, we use the assumption that speech can be plausibly modeled by a Laplace distribution and develop a practical approximation of Laplace ...
But with the generalization of the idea to non-Gaussian speech signals, the joint entropy based new multichannel TDE algorithm manifests a potential to outperform the MCCC-based method. ...
In this paper, the concept of minimum entropy is introduced and a novel entropy-based multichannel TDE algorithm is developed. ...
doi:10.1109/icassp.2007.366629
dblp:conf/icassp/HuangBC07
fatcat:fhip7mx47rhqdphtt23jmmkk6m
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