IEEE Organizations related to Information Entropy

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Conferences related to Information Entropy

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2020 IEEE 23rd International Conference on Information Fusion (FUSION)

The International Conference on Information Fusion is the premier forum for interchange of the latest research in data and information fusion, and its impacts on our society. The conference brings together researchers and practitioners from academia and industry to report on the latest scientific and technical advances.


2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

All topics related to engineering and technology management, including applicable analytical methods and economical/social/human issues to be considered in making engineering decisions.


2020 IEEE International Radar Conference (RADAR)

Everything to do with radar hardware, techniques, processing and systems.

  • 2019 International Radar Conference (RADAR)

    RADAR2019 is in the frame of the international relations set up between the IET, the IEEE, the CIE, the IEAust and the SEE. The conference will focus on new research and developments in the fields: Radar Systems (ground based, airborne, spaceborne), Radar Environment and Phenomenology, Electromagnetic Modeling Radar Component Technologies, Remote Sensing from Airborne or Spaceborne Systems, SAR & ISAR Imagery Waveform design, beamforming and signal processing Emerging, Radar Applications, Smart Visualization and Information processing, System Modeling, Simulation and Validation, Radar Management Techniques Automatic Classification. The conference will take place at Toulon Neptune Palais. Located on the French Riviera, Toulon is an important centre for naval construction and aeronautical equipment,hosting the major naval centre on France's Mediterranean coast, also home of the French Navy aircraft carrier Charles De Gaulle.

  • 2018 International Conference on Radar (RADAR)

    All aspects of radar systems for civil and defence applications.

  • 2017 International Radar Conference (Radar)

    radar environment and phenomenology, radar systems, remote sensing from airborne or spaceborne systems, waveform design, beamforming and signal processing, emerging technologies, advanced sub-systems technologies, computer modelling, simulation and validation, radar management techniques

  • 2016 CIE International Conference on Radar (RADAR)

    The 2016 CIE International Conference on Radar (Radar 2016) will be held in October 10-13 in Guangzhou, China. Radar 2016 is one of the international radar conference series which is held separately in USA, China, UK, Australia and France. It is the 7th International Radar Conference held in China. The conference topics of Radar 2016 will cover all aspects of radar system for civil or defense application.The professional theme of Radar 2016 is “Innovative thinking into the future”. It is our pleasure and honor to invite you to attend Radar 2016 conference. All accepted papers will be published in the conference proceedings We hope to meet you in Guangzhou, China.

  • 2014 International Radar Conference (Radar)

    Radar 2014 cover all aspects of radar systems for civil, security and defence application. Waveform design, beamforming, signal processing, Emerging applications and technologies, sub-systems technologies, Radar environment.

  • 2013 International Conference on Radar

    Radar 2013 cover all aspects of radar systems for civil, security and defence application. Waveform design, beamforming, signal processing, Emerging applications and technologies, sub-systems technologies, Radar environment.

  • 2012 International Radar Conference (Radar)

    Radar Environment/Phenomenology, Radar Systems, Remote Sensing from Airborne/Spaceborne Systems, Waveform Design, Beamforming/Signal Processing, Emerging Applications, Advanced Sub-Systems, Computer Modelling, Simulation/Validation.

  • 2011 IEEE CIE International Conference on Radar (Radar)

    This series of successfully organized international conference on radar shows the very fruitful cooperation between IEEE AESS, IET/UK, SEE/France, EA/Australia CIE/China, and the academy societies of other countries , such as Germany, Russia, Japan, Korea and Poland. Radar 2011 is a forum of radar engineers and scientists from all over the world. The conference topics of Radar 2011 will cover all aspects of radar system for civil and defense applications.

  • 2009 International Radar Conference Radar "Surveillance for a Safer World" (RADAR 2009)

    The conference will focus on new research and developments in the field of radar techniques for both military and civil applications. Topics to be covered at Radar 2009 include: Radar Environment and Phenomenology Radar Systems Remote Sensing from Airborne or Spaceborne Systems Waveform Design, Beamforming and Signal Processing Emerging Radar Applications Emerging Technologies Advanced Sub-Systems Technologies Computer Modeling, Simulation and V

  • 2008 International Conference on Radar (Radar 2008)

    All aspects of radar systems for civil, security and defence applications. Themes include: Radar in the marine environment, Radar systems, Multistatic and netted radars, Radar subsystems, Radar techniques, processing and displays, Modelling and simulation of radar environments, Electronic attack, Electronic protection, Test and Evaluation

  • 2003 IEEE International Radar Conference


2020 IEEE International Symposium on Information Theory (ISIT)

Information theory, coding theory, communication theory, signal processing, and foundations of machine learning


ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

The ICASSP meeting is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and over 50 lecture and poster sessions.


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Periodicals related to Information Entropy

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Most published Xplore authors for Information Entropy

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Xplore Articles related to Information Entropy

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Optimal Non-Uniform Mapping for Probabilistic Shaping

SCC 2013; 9th International ITG Conference on Systems, Communication and Coding, 2013

The construction of optimal non-uniform mappings for discrete input memoryless channels (DIMCs) is investigated. An efficient algorithm to find optimal mappings is proposed and the rate by which a target distribution is approached is investigated. The results are applied to non-uniform mappings for additive white Gaussian noise (AWGN) channels with finite signal constellations. The mappings found by the proposed methods ...


Unsupervised feature selection based on Markov blanket and particle swarm optimization

Journal of Systems Engineering and Electronics, 2017

Feature selection plays an important role in data mining and recognition, especially in the large scale text, image and biological data. Specifically, the class label information is unavailable to guide the selection of minimal feature subset in unsupervised feature selection, which is challenging and interesting. An unsupervised feature selection based on Markov blanket and particle swarm optimization is proposed named ...


A Chinese Text Watermarking Based on Statistic of Phrase Frequency

2008 International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2008

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 ...


Key frame extraction based on information entropy and edge matching rate

2010 2nd International Conference on Future Computer and Communication, 2010

This paper presents a new approach for key frame extraction based on the image information entropy and edge matching rate. Firstly, the information entropy of every frame is calculated, and then the edges of the candidate key frames are extracted by Prewitt operator. At last, the paper makes the edges of adjacent frames match. If the edge matching rate is ...


A Physical Education Teaching Quality Evaluation Method Based on Entropy Model

2013 Fourth International Conference on Intelligent Systems Design and Engineering Applications, 2013

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, ...


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Educational Resources on Information Entropy

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IEEE-USA E-Books

  • Optimal Non-Uniform Mapping for Probabilistic Shaping

    The construction of optimal non-uniform mappings for discrete input memoryless channels (DIMCs) is investigated. An efficient algorithm to find optimal mappings is proposed and the rate by which a target distribution is approached is investigated. The results are applied to non-uniform mappings for additive white Gaussian noise (AWGN) channels with finite signal constellations. The mappings found by the proposed methods outperform those obtained via a central limit theorem approach as suggested in the literature.

  • Unsupervised feature selection based on Markov blanket and particle swarm optimization

    Feature selection plays an important role in data mining and recognition, especially in the large scale text, image and biological data. Specifically, the class label information is unavailable to guide the selection of minimal feature subset in unsupervised feature selection, which is challenging and interesting. An unsupervised feature selection based on Markov blanket and particle swarm optimization is proposed named as UFSMB-PSO. The proposed method seeks to find the high-quality feature subset through multi-particles' cooperation of particle swarm optimization without using any learning algorithms. Moreover, the features' relevance will be computed based on an information metric of relevance gain, which provides an information theoretical foundation for finding the minimization of the redundancy between features. Our results on several benchmark datasets demonstrate that UFSMB-PSO can achieve significant improvement over state of the art unsupervised methods.

  • 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.

  • Key frame extraction based on information entropy and edge matching rate

    This paper presents a new approach for key frame extraction based on the image information entropy and edge matching rate. Firstly, the information entropy of every frame is calculated, and then the edges of the candidate key frames are extracted by Prewitt operator. At last, the paper makes the edges of adjacent frames match. If the edge matching rate is up to 50%, the current frame is deemed to the redundant key frame and should be discarded. The experimental results show that the method proposed in this paper is accurate and effective for key frame extraction, and the extracted key frames can be a good representative of the main content of the given video.

  • 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.

  • Research on Module Partition and Solution Evaluation Method Based on the Interface Relationship

    Module division is the basis for product modularization. The rationality of the product module division directly affects the function, performance, development time, cost, general degree of module, convenience of maintenance and so on. A module partition method has been proposed based on the interface relationship of Pros and Cons. It parted the module using fuzzy theory, based on the qualitative hierarchy decomposition of the function, considering the interface depending factors of the parts at the same time in this method. And it introduced "information entropy" concept to evaluate the different module partition schemes, then choose the best module partition scheme. Finally, an example validated the method.

  • Power system risk security assessment based on maximum information entropy principle

    This paper presents a new method for risk assessment of the power system security. The maximum information entropy principle is introduced to acquire the probability distribution of component's fault. So the probability of the power system fault is obtained by power system fault model. The electric betweenness is added to the severity index as the weight of component, which reflects the severity of different faults to the power system. Lastly, in the combination with the probability of power system fault and the severity index, the power system risk assessment model is established. This method overcomes the shortcomings of the traditional risk assessment methods that couldn't find the accurate power system fault probability which is a small probability event from the limited historical data. At last, the validity and feasibility of proposed method is verified by the calculation result of IEEE-30 system.

  • Attribute reduction based on improved discernibility matrix

    The attribute reduction based on information entropy is different to that based on positive region in inconsistent information system. The problem of discernibility matrix in algebra view is analyzed, and an new discernibility matrix based on information entropy is proposed in this paper. This algorithm considers whether the objects compared are consistent, analyses in detail the degree of inconsistency and the distributing proportion of their conditional equivalent classes in decision classes, and the reduction based on information entropy is acquired finally. The theoretic analysis and simulation instance shows that this algorithm is feasible and effective in practice.

  • Research on Intrusion Detection Technology Based on Immune Algorithm

    By analyzing and improving the artificial immune algorithm based on information entropy and Euclidean distance, a novel artificial immune algorithm used in intrusion detection (AIAID) is proposed. The core of the algorithm lies on improving the calculation about similarity and expected breed rate by the principle of Mahalanobis distance, namely introducing the importance and value range of antibody attributes into correlation computing. And algorithm flow is optimized. Then a new model for intrusion detection system is designed by using AIAID. The tests indicate that using AIAID in intrusion detection can obviously shorten training time and improve detection efficiency.

  • Research on the Pre-warning Model of Enterprise Financial Crisis Based on the Information Entropy and PSO-ANN

    The pre-warning of enterprise financial crisis is a hot studying spot in current theoretical field. This paper firstly overviews the present research conditions of enterprise financial crisis pre-warning, sets up a more perfect pre-warning indicators system. Then accomplishes dynamic pre-warning for the financial risk based on the great nonlinear function approaching capability of artificial nerve network(ANN). To simplify the space dimension of input information and reduce the complexity of network structure, the information entropy reduction theory is brought in. At the same time, aim at the main shortage of ANN (the converging speed is often slow and the network is easily involved in local optimum), this paper introduces the Particle Swarm Optimization(PSO). Thus establishing a pre-warning system to enterprise financial crisis based on the information entropy and the PSO-ANN, making the information reduction, the dynamic study and induction of ANN, the particle swarm optimization, the forecast and evaluation of enterprise financial crisis organically combined. At last, an actual example is given to justify the validity and efficiency of this model. The study can supplies a new means for the dynamic pre-warning of enterprise financial crisis.



Standards related to Information Entropy

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Jobs related to Information Entropy

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