IEEE Organizations related to Correlation Coefficient

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Conferences related to Correlation Coefficient

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2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting

The joint meeting is intended to provide an international forum for the exchange of information on state of the art research in the area of antennas and propagation, electromagnetic engineering and radio science


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 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.


2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

The Conference focuses on all aspects of instrumentation and measurement science andtechnology research development and applications. The list of program topics includes but isnot limited to: Measurement Science & Education, Measurement Systems, Measurement DataAcquisition, Measurements of Physical Quantities, and Measurement Applications.


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 Correlation Coefficient

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Most published Xplore authors for Correlation Coefficient

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Xplore Articles related to Correlation Coefficient

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Limits on the complexity of empirical models of magnetic storm phenomena

Space Weather, 2006

We explore the statistical limits on the complexity of data-derived models of magnetic storm phenomena, including magnetic indices, plasmapause evolution, and outer radiation belt dynamics. Specifically, we estimate the limits on the number of free parameters justifiable by application of Occam's razor, or the rule of parsimony. These limits arise from the strong intercorrelation of geomagnetic phenomena, which decimates the ...


User Electricity Consumption Pattern Optimal Clustering Method for Smart Gird

2018 14th IEEE International Conference on Signal Processing (ICSP), 2018

To select the optimal number of clusters for the user's intelligent behavior in the context of big data, a cluster number optimization method for user behavior analysis is proposed. Firstly, this paper is based on the research of feature optimization method for the behavior analysis of intelligent electricity users in the early stage. Then, the optimal cluster number selection method ...


An Approach to N-Gram Language Model Evaluation in Phrase-Based Statistical Machine Translation

2012 International Conference on Asian Language Processing, 2012

N-gram Language model plays an important role in statistical machine translation. Traditional methods adopt perplexity to evaluate language models, while this metric does not consider the characteristics of statistical machine translation. In this paper, we propose a novel method, namely bag-of-words decoding, to evaluate n-gram language models in phrase-based statistical machine translation. As compared with perplexity, our approach has more ...


Comparable estimation of network power for chi-squared Pearson functional networks and Bayes hyperbolic functional networks while processing biometric data

2017 International Siberian Conference on Control and Communications (SIBCON), 2017

This paper aims at the comparison of the network power for Pearson-Hamming networks built using the chi-squared functional set, and Bayes-Hamming networks built using the hyperbolic functional set. To configure these networks a correlation matrix of biometric data is calculated. At the nest step the data are sorted. Low-correlated data are converted with Pearson- Hamming networks, high-correlated data are converted ...


Reducing Forged Features Using Tampered and Inconsistent Image Detection Techniques in Digital Image Processing

2015 Fifth International Conference on Communication Systems and Network Technologies, 2015

The fast advent and development of numerous low cost commercial image editing software, distortions in image are easy and its quick recognition and identification is very hard. This has resulted in digital image manipulations (also known as forgery and meddling) which alters the original image and hides or removes meaningful information and makes it tampered. All this is done with ...


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Educational Resources on Correlation Coefficient

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IEEE-USA E-Books

  • Limits on the complexity of empirical models of magnetic storm phenomena

    We explore the statistical limits on the complexity of data-derived models of magnetic storm phenomena, including magnetic indices, plasmapause evolution, and outer radiation belt dynamics. Specifically, we estimate the limits on the number of free parameters justifiable by application of Occam's razor, or the rule of parsimony. These limits arise from the strong intercorrelation of geomagnetic phenomena, which decimates the effective sample size of independent observations of magnetic storm phenomena. We show that the resulting paucity of distinct magnetic storms over the history of magnetic indices and satellite observations severely limits the justifiable complexity of data-derived models. Our analysis applies to a wide variety of models with a finite number of constant free parameters but not to models with time- varying parameters nor to nearest-neighbors models.

  • User Electricity Consumption Pattern Optimal Clustering Method for Smart Gird

    To select the optimal number of clusters for the user's intelligent behavior in the context of big data, a cluster number optimization method for user behavior analysis is proposed. Firstly, this paper is based on the research of feature optimization method for the behavior analysis of intelligent electricity users in the early stage. Then, the optimal cluster number selection method is proposed in this paper, and the optimal cluster number is determined by considering the accuracy rate index and correlation coefficient index comprehensively. Finally, this paper takes Irish electricity data as data source to carry out experimental simulation. The simulation results show that the proposed method can select a reasonable number of clusters and effectively improve the data clustering effect of the analysis of electrical behavior.

  • An Approach to N-Gram Language Model Evaluation in Phrase-Based Statistical Machine Translation

    N-gram Language model plays an important role in statistical machine translation. Traditional methods adopt perplexity to evaluate language models, while this metric does not consider the characteristics of statistical machine translation. In this paper, we propose a novel method, namely bag-of-words decoding, to evaluate n-gram language models in phrase-based statistical machine translation. As compared with perplexity, our approach has more remarkable correlation with translation quality measured by BLEU. Experimental results on NIST data sets demonstrate the effectiveness of our method.

  • Comparable estimation of network power for chi-squared Pearson functional networks and Bayes hyperbolic functional networks while processing biometric data

    This paper aims at the comparison of the network power for Pearson-Hamming networks built using the chi-squared functional set, and Bayes-Hamming networks built using the hyperbolic functional set. To configure these networks a correlation matrix of biometric data is calculated. At the nest step the data are sorted. Low-correlated data are converted with Pearson- Hamming networks, high-correlated data are converted using Bayes-Hamming networks. The detection of a pair with high-correlated parameters r ≈ 0.99 is equal to the detection of approximately 9 pairs of low-correlated parameters r ≈ 0. The power gain for Pearson-Hamming and Bayes-Hamming networks are comparable. Low-correlated parameters dominate but they are less significant than high-correlated parameters.

  • Reducing Forged Features Using Tampered and Inconsistent Image Detection Techniques in Digital Image Processing

    The fast advent and development of numerous low cost commercial image editing software, distortions in image are easy and its quick recognition and identification is very hard. This has resulted in digital image manipulations (also known as forgery and meddling) which alters the original image and hides or removes meaningful information and makes it tampered. All this is done with a malicious motivation to change the originality of image. Over the past decades a very promising field called as the field of digital forensics has emerged to help restore some trust to digital images. Restoring the traditional trustworthiness on digital photos plays prominent role as doctored photos are enhancing with growing frequency and sophistication these days .In this paper, we focus on image forensic detection on tampered pictures. The detection of a tampering in image is driven to provide authenticity and to maintain integrity of the image so that tampering is detected and minimized.

  • Acoustic beam-based man-made underwater landmark detection method for multi-beam sonar

    We proposed man-made underwater landmark and acoustic beam-based landmark detection method. Beams in multi-beam sonar are independent each other, and each beam can be assumed as a feature to distinguish interesting area. When beam passes the object, the column array of sonar image is composed highlighted and shadow areas. Using these property, it is possible to recognize the underwater landmark by beam-based detection method. The performance of the proposed method is verified through experimental results, and this method can be applied to autonomous underwater vehicles' navigation.

  • An optimized cross correlation power attack of message blinding exponentiation algorithms

    The message blinding method is the most efficient and secure countermeasure against first-order differential power analysis(DPA). Although cross correlation attacks(CCAs) were given for defeating message blinding methods, however searching for correlation points is difficult for noise, misalignment in practical environment. In this paper, we propose an optimized cross correlation power attack for message blinding exponentiation algorithms. The attack method can select the more correlative power points of share one operation in the modular multiplication by comparing variances between correlation coefficients. Further we demonstrate that the attack method is more efficient in experiments with hardware implementation of RSA on a crypto chip card. In addition to the proposed CCA method can recovery all 1024bits secret key and recognition rate increases to 100% even when the recorded signals are noisy.

  • The Prediction of Petroleum Pipeline Data Based on Matrix Rotation-Generalized Regression Neural Network

    This paper presents a new approach for petroleum pipeline data prediction. In order to obtain correlation coefficient matrix of variables of petroleum pipeline monitoring data monthly, a novel method of matrix rotation- generalized regression neural network for petroleum pipeline data prediction is proposed. The simulation analysis demonstrates that the model is not only more precise, but also more effective and feasible.

  • Ultra wideband antennas for high data rate and low mutual coupling using circular reflector

    A MIMO (multiple input multiple output) antennas for two different shapes has been designed and studied, different isolation techniques has been analyzed in order to reduce mutual coupling between two elements. Initially, a tiny sized hexagonal shaped patch for wideband operation is designed in two MIMO elements format, a current distribution study has been carried out to reduce mutual coupling. Later on circular patch MIMO of two antenna elements for UWB (Ultra- wideband) application is designed and analyzed. Same structure is suspended to different isolation techniques; a large reduction in radiation interference is seen. An analysis based study on different isolation techniques done in order to get better reduction in mutual coupling, Along with these study necessary parameters for UWB MIMO antenna like Gain variation and correlation coefficient has been presented.

  • Hand gesture recognition for Lao alphabet sign language using HOG and correlation

    Hand gesture is one of a powerful means of communication among human. Sign language is an essential and natural expressive mean of communication especially for the deaf people. The article proposes a technique for the recognition of Lao alphabet sign language. The technique of image processing, that is Histogram of Oriented Gradients (HOG), is applied in order to extract characteristics of the hand images performing individual alphabet of Lao sign language. The extracted features are then sent to the template matching process. The similarity between the extracted features and the prototype features are measured by using correlation technique. The totals of 54 Lao alphabets are used in the experiments. Four subjects are asked to perform each alphabet of Lao sign language in which each subject had performed totally 540 gestures. The recognition rate of the proposed technique at about 79 % is achieved.



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