Entropy

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Entropy is a thermodynamic property that can be used to determine the energy available for useful work in a thermodynamic process, such as in energy conversion devices, engines, or machines. (Wikipedia.org)






Conferences related to Entropy

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ICC 2021 - IEEE International Conference on Communications

IEEE ICC is one of the two flagship IEEE conferences in the field of communications; Montreal is to host this conference in 2021. Each annual IEEE ICC conference typically attracts approximately 1,500-2,000 attendees, and will present over 1,000 research works over its duration. As well as being an opportunity to share pioneering research ideas and developments, the conference is also an excellent networking and publicity event, giving the opportunity for businesses and clients to link together, and presenting the scope for companies to publicize themselves and their products among the leaders of communications industries from all over the world.


2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE


2020 59th IEEE Conference on Decision and Control (CDC)

The CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.


2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and severalco-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students, academics and industry researchers.

  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conferenceand 27co-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students,academics and industry.

  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    computer, vision, pattern, cvpr, machine, learning

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. Main conference plus 50 workshop only attendees and approximately 50 exhibitors and volunteers.

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Topics of interest include all aspects of computer vision and pattern recognition including motion and tracking,stereo, object recognition, object detection, color detection plus many more

  • 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Sensors Early and Biologically-Biologically-inspired Vision, Color and Texture, Segmentation and Grouping, Computational Photography and Video

  • 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics, motion analysis and physics-based vision.

  • 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics,motion analysis and physics-based vision.

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2005 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


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Periodicals related to Entropy

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Audio, Speech, and Language Processing, IEEE Transactions on

Speech analysis, synthesis, coding speech recognition, speaker recognition, language modeling, speech production and perception, speech enhancement. In audio, transducers, room acoustics, active sound control, human audition, analysis/synthesis/coding of music, and consumer audio. (8) (IEEE Guide for Authors) The scope for the proposed transactions includes SPEECH PROCESSING - Transmission and storage of Speech signals; speech coding; speech enhancement and noise reduction; ...


Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Circuits and Systems for Video Technology, IEEE Transactions on

Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...


Circuits and Systems I: Regular Papers, IEEE Transactions on

Part I will now contain regular papers focusing on all matters related to fundamental theory, applications, analog and digital signal processing. Part II will report on the latest significant results across all of these topic areas.


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Most published Xplore authors for Entropy

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Xplore Articles related to Entropy

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Application and evaluation on combination forecasting model based on information entropy and Shapley value

2011 International Conference on Consumer Electronics, Communications and Networks (CECNet), 2011

The key problem of combination forecasting model is the weight of the single prediction methods. The values of the weights directly effect the accuracy of combination forecasting model. In this paper, taking agricultural machine total power in Heilongjiang province as original data, the three combination forecasting models were obtained through respectively using shapley value, information entropy and combining information entropy ...


Research on land-use structure in the water-level-fluctuating zone of Three Gorges Reservoir area based on information entropy — A case study of Kaixian County in Chongqing City, China

2011 International Conference on Remote Sensing, Environment and Transportation Engineering, 2011

According to the operation of Three Gorges Project, a water-level-fluctuating zone with 30m high will come into being in Three Gorges Reservoir Area, which will bring a succession of ecological and environmental problems. Therefore the research on the land-use structure of water-level-fluctuating zone is very important for environmental protection in Three Gorges Reservoir Area. Using the land use data and ...


Flow pattern identification of gas-liquid flow based on the hybrid model of multi-scale information entropy feature and LS-SVM

2008 7th World Congress on Intelligent Control and Automation, 2008

Based on the characteristic that the Empirical Mode Decomposition (EMD) can decompose signal adaptively, a flow pattern identification method based on EMD multi-scale information entropy was put forward. Firstly, the acquired pressure-difference fluctuation signals are decomposed through EMD, and the decomposed signals within different frequency bands are obtained adaptively. Secondly, the multi-scale information signal entropy eigenvectors of flow pattern are ...


Generalized Context Transformations -- Enhanced Entropy Reduction

2015 Data Compression Conference, 2015

Context transformations is a very simple data transformation method that we presented recently and it is used to decrease uncertainty in input data. The transformation is based on exchange of two different di-grams. This paper is focused on new consequences of the relationships discovered subsequently. We were able to find a mathematical model which predicts the efficiency of each transformation. ...


Grammatical Ziv-Lempel Compression: Achieving PPM-Class Text Compression Ratios with LZ-Class Decompression Speed

2016 Data Compression Conference (DCC), 2016

Summary form only given: GLZA is a free, open-source, enhanced grammar-based compressor that constructs a low entropy grammar amenable to entropy coding, using a greedy hill-climbing search guided by estimates of encoded string lengths; the estimates are efficiently computed incrementally during (parallelized) suffix tree construction in a batched iterative repeat replacement cycle. The grammar-coded symbol stream is further compressed by ...


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Educational Resources on Entropy

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IEEE-USA E-Books

  • Application and evaluation on combination forecasting model based on information entropy and Shapley value

    The key problem of combination forecasting model is the weight of the single prediction methods. The values of the weights directly effect the accuracy of combination forecasting model. In this paper, taking agricultural machine total power in Heilongjiang province as original data, the three combination forecasting models were obtained through respectively using shapley value, information entropy and combining information entropy with shapley value to calculate weights of each single models. The combination forcasting model based on combining shapley value with information entropy after evaluation could get the highest prediction accuracy.

  • Research on land-use structure in the water-level-fluctuating zone of Three Gorges Reservoir area based on information entropy — A case study of Kaixian County in Chongqing City, China

    According to the operation of Three Gorges Project, a water-level-fluctuating zone with 30m high will come into being in Three Gorges Reservoir Area, which will bring a succession of ecological and environmental problems. Therefore the research on the land-use structure of water-level-fluctuating zone is very important for environmental protection in Three Gorges Reservoir Area. Using the land use data and remote sensing image from 2003 to 2009 in Kaixian County which holds the biggest area of water-level-fluctuating zone, this paper adopts the information entropy model to analyze the dynamic changes of land- use system's order degree during the process of forming the Reservoir, and simulates five kinds of land use pattern. The results showed as following: 1) with the upgrade of reservoir water level, the entropy of land use system is increasing. It demonstrates that the land use structure is in higher order relatively in 2003, and land use disorder increased highly in 2009. 2) The wetland protection pattern is the optimal pattern in four simulation patterns. At the same time, it confirmed the importance of wetland protection in urban edge. Although the current “dam” pattern is sub-optimal, its ecological and economic benefits are relatively reasonable. Therefore current “dam” pattern is acceptable.

  • Flow pattern identification of gas-liquid flow based on the hybrid model of multi-scale information entropy feature and LS-SVM

    Based on the characteristic that the Empirical Mode Decomposition (EMD) can decompose signal adaptively, a flow pattern identification method based on EMD multi-scale information entropy was put forward. Firstly, the acquired pressure-difference fluctuation signals are decomposed through EMD, and the decomposed signals within different frequency bands are obtained adaptively. Secondly, the multi-scale information signal entropy eigenvectors of flow pattern are abstracted. Finally, those eigenvectors are fed into the established hybrid model of EMD and LS-SVM for flow pattern identification and thus the flow pattern intelligent identification is realized. The experimental results show that this method can precisely identify the flow patterns of bubble flow, plug flow, and churn flow, respectively.

  • Generalized Context Transformations -- Enhanced Entropy Reduction

    Context transformations is a very simple data transformation method that we presented recently and it is used to decrease uncertainty in input data. The transformation is based on exchange of two different di-grams. This paper is focused on new consequences of the relationships discovered subsequently. We were able to find a mathematical model which predicts the efficiency of each transformation. The new type of the transformation, Generalized context transformation, developed recently is more efficient than the previous one and it is able to remove almost all redundancy based on the symbols mutual information. The newly developed algorithm is computationally and entropic ally more efficient than the previous one.

  • Grammatical Ziv-Lempel Compression: Achieving PPM-Class Text Compression Ratios with LZ-Class Decompression Speed

    Summary form only given: GLZA is a free, open-source, enhanced grammar-based compressor that constructs a low entropy grammar amenable to entropy coding, using a greedy hill-climbing search guided by estimates of encoded string lengths; the estimates are efficiently computed incrementally during (parallelized) suffix tree construction in a batched iterative repeat replacement cycle. The grammar-coded symbol stream is further compressed by order-1 Markov modeling of trailing/leading subsymbols and selective recency modeling, MTF-coding only symbols that tend to recur soon. This combination results in excellent compression ratios-similar to PPMC's for small files, averaging within about five percent of PPMd's for large text files (1 MB - 10 MB)-with fast decompression on one core or two. Compression time and memory use are not dramatically higher than for similarly high-performance asymmetrical compressors of other kinds. GLZA is on the Pareto frontier for text compression ratio and decompression speed on a variety of benchmarks (LTCB, Calgary, Canterbury, Large Canterbury, Silesia, Maximum Compression, World Compression Challenge), compressing better and/or decompressing faster than its competitors (PPM, LZ77-Markov, BWT, etc.), with better compression ratios than previous grammar-based compressors such as RePair, Sequitur, Offline 3 (Greedy), Sequential/grzip, and IRR-S.

  • On Achievable Rates Over Time-Varying Rayleigh Fading Channels

    None

  • A Chinese Text Watermarking Based on Statistic of Phrase Frequency

    Although tamper and delete attack problem is difficult to overcome, this paper proposes a novel algorithm based on the statistical characteristics of phrase frequency to solve it. The algorithm takes watermark as information entropy and Chinese characters' code as partial probability distribution values. As a result, the problem of sequence absence brought by delete attack is converted into sorting order changing problem. To approximate watermark information entropy, two approximation algorithms are presented, the performance of which were also analyzed. Moreover after being organized in cyclic codes, the rest probability distribution value is embedded in cover text. Not only does cyclic code with redundancy guarantee the overall data safety, but error correction reduces delete attack impact.

  • Appraisal on the third party logistics enterprises’ core competence

    With the embedded development of logistics theory and practice, the third party logistics (TPL) appeared. Itpsilas a new logistics form and itpsilas the result of professional and integrative logistics. The rapid development of economics global process and application of information technology makes more and more enterprises inclined to put the logistics outsourcing to the third party logistics enterprises. The third party logistics will be the mainstream of logistics development in the 21st century. So, the appraisal to the third party logistics enterprisepsilas core competence is imperative under the situation. The paper analyzed the third party logistics enterprisepsilas core competence, and established the index system of third party logistics enterprisepsilas core competence. On the basis of investigation about indexes of the third party logistics enterprisepsilas core competence, it applied information entropy to reduce index system, and found out more proper appraisal indexes of the third party logistics enterprises. Then it applied improved BP neutral network to appraise the third party logistics enterprisepsilas core competence. Via case analysis, proved this methodpsilas tangibility and validity to appraise the third party logistics enterprisepsilas core competence.

  • Emissivity and Temperature Assessment Using a Maximum Entropy Estimator: Structure and Performance of the MaxEnTES Algorithm

    In this paper, we discuss the structure and performance of the maximum entropy temperature-emissivity separation (MaxEnTES) algorithm for assessing land temperature and emissivity from thermal infrared hyperspectral images. This procedure derives the emissivity spectrum and the temperature of the target adopting the maximum entropy (MaxEnt) estimation approach. The main advantage of the MaxEnt statistical inference is the absence of any external hypothesis, which is, instead, the main critical point characterizing any other temperature-emissivity separation (TES) algorithm. The MaxEnTES algorithm carries out the TES task adopting a modified version of the subgradient Shor's r-algorithm adopted for numerical optimization of a MaxEnt objective function. For this purpose, we have utilized the C/C++ Solvopt code from the University of Gratz to develop a practical data processing implementation. In this paper, we discuss the mathematical structure of the MaxEnTES algorithm and analyze its performance in depth using numerical simulations and remote sensing Multispectral Infrared/Visible Imaging Spectrometer images. We show that the MaxEnTES algorithm provides improved accuracy for temperature and emissivity estimation, lowering the standard estimation error to a fraction of degree Kelvin. In agreement with previous investigations, we find that the estimation accuracy grows when increasing the number of available spectral channels. The systematic errors affecting the temperature estimates (e.g., bias) are thoroughly evaluated. We prove that the MaxEnTES algorithm retrieves the correct shape of the target emissivity spectrum even in presence of a significant temperature estimation error.

  • A Physical Education Teaching Quality Evaluation Method Based on Entropy Model

    In this paper, we study on evaluating physical education teaching quality based on the entropy model. The entropy model is a measure of the uncertainty associated with a random variable, which is a powerful tool in many research fields. Next, a physical education teaching quality evaluation method is designed by obtaining the maximum information entropy based on the index systems, which include 12 categories index, such as include continuous variables effect factors and discrete variables effect factors. To demonstrate the effectiveness of the proposed method in physical education teaching quality evaluation, an experiment is conducted on ten datasets to make performance evaluation comparing with the results obtained by the students evaluation and experts evaluation.



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