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Synthetic aperture radar (SAR) image segmentation using a new modified fuzzy c-means algorithm

Synthetic aperture radar (SAR) image segmentation using a ne...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Chumsamrong, W Thitimajshima, P Rangsanseri, Y King Mongkuts Inst Technol Ladkrabang Fac Engn Dept Telecommun Engn Bangkok 10520 Thailand

ISBN: (纸本)0780363590

Generally fuzzy c-means algorithm is one proved that very well suited for remote sensing image segmentation. exhibited sensitivity to the initial guess with regard to both speed and stability. But it also showed sensitivity to noise. This paper proposes a fully automatic technique to obtain image clusters. A modified fuzzy c-means classification algorithm is used to provide a fuzzy partition. This method is less sensitive to noise as it filters the image while clustering it, which is based on the consideration of the neighbors as factors the attract pixels into their cluster, The experimental results on JERS-1 Synthetic Aperture Radar (SAR) image demonstrate its potential usefulness.

关键词： Synthetic aperture radar image segmentation fuzzy partition sorting algorithm Fuzzy Image JERS

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An Open-source Toolbox For Standardized Use Of PhysioNet Sleep EDF Expanded Database 37

An Open-source Toolbox For Standardized Use Of PhysioNet Sle...

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37th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Imtiaz, Syed Anas Rodriguez-Villegas, Esther Univ London Imperial Coll Sci Technol & Med Elect & Elect Engn Dept Circuits & Syst Grp London SW7 2AZ England

ISBN: (纸本)9781424492701

PhysioNet Sleep EDF database has been the most popular source of data used for developing and testing many automatic sleep staging algorithms. However, the recordings from this database has been used in an inconsistent fashion. For example, arbitrary selection of start and end times from long term recordings, data-hypnogram mismatches, different performance metrics and hypnogram conversion from R&K to AASM. All these differences result in different data sections and performance metrics being used by researchers thereby making any direct comparison between algorithms very difficult. Recently, a superset of this database has been made available on PhysioNet, known as the Sleep EDF Expanded Database which includes 61 recordings. This provides an opportunity to standardize the way in which signals from this database should be used. With this goal in mind, we present in this paper a toolbox for automatically downloading and extracting recordings from the Sleep EDF Expanded database and converting them to a suitable format for use in MATLAB. This toolbox contains functions for selecting appropriate data for sleep analysis (based on our previous recommendations for sleep staging), hypnogram conversion and computation of performance metrics. Its use makes it simpler to start using the new sleep database and also provides a foundation for much-needed standarization in this research field.

关键词： database management systems medical administrative data processing public domain software AASM Matlab automatic sleep staging algorithms data source data-hypnogram mismatches hypnogram conversion open-source toolbox performance metrics physionet sleep EDF expanded database sleep analysis algorithm design and analysis Classification algorithms Databases Electroencephalography MATLAB Sleep Database Performance metrics MATLAB algorithm design and analysis open source software Data sources Sleep sorting algorithm database management systems Interleukin-5 European Development Fund Electroencephalography tool cases

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Average Likelihood Method for Classification of CDMA 33

Average Likelihood Method for Classification of CDMA

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33rd Annual IEEE Military Communications Conference on Affordable Mission Success - Meeting the Challenge (MILCOM)

作者： Irizarry, Alfredo Vega Fam, Adly Air Force Res Lab Rome NY 13441 USA SUNY Buffalo New York NY USA

ISBN: (纸本)9781479967704

A new algorithm for classifying Direct Sequence Code Division Multiple Access (DS-CDMA) signals in additive white Gaussian noise (AGWN) is proposed based on the average likelihood (AL) function. The AL is express in terms of the code length and the number of active users. These parameters constitute the hypothesis under test. While the AL function is expressed in an analytical form, the implementation requires knowledge on the spreading codes that acchive a low Total Squared Correlation (TSC) value. This complexity can be simplified by developing a hard decision scheme which only requires knowledge on matrices that achieve the lowest TSC. Our study cases include binary and multiclass classification using full loaded DS-CDMA with knowledge onf the chip period. Code lengths of powers of 2 are used as a proof of concept.

关键词： AWGN code division multiple access codes matrix algebra signal classification spread spectrum communication AGWN AL function method DS-CDMA signal classification additive white Gaussian noise average likelihood function method binary classification chip period code length direct sequence code division multiple access signal classification hard decision scheme low total squared correlation value multiclass classification number-of-active users spreading codes Classification algorithms Complexity theory Correlation Error correction Error correction codes Multiaccess communication Vectors AWGN Code division multiple access code length spreading code Multi access systems Error correction codes sorting algorithm Spread spectrum communication signal classification Complexity theory Direct-sequence code-division multiple access matrix algebra error correction

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Cascaded H-bridge Converter Integrated with Split Batteries and with Multilevel AC Output for Household Applications 39

Cascaded H-bridge Converter Integrated with Split Batteries ...

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Applied Power Electronics Conference and Exposition (APEC)

作者： Alimawi, Madhat Eskandari, Reyhaneh Venugopal, Prasanth Soeiro, Thiago Batista Univ Twente Fac EEMCS Enschede Netherlands Univ Nottingham Fac Engn Nottingham England

ISBN: (纸本)9798350316643

This study presents a 6-module cascaded Hbridgemultilevel converter design for AC split batteries in residential applications. It incorporates sorting-based balancing and level-shifted modulation for reduced harmonic distortion and current ripple. Two current controllers, PR and dq controllers, are employed for grid synchronization and quality control, with a focus on comparing their performance in terms of harmonic distortion, settling time, and steady-state error. Simulation results validate the effectiveness of sub-batteries balancing method during charging and discharging, and the stability of both controllers against the 5th and 7th harmonic distortion. Additionally, an experimental prototype with 6 battery emulators confirms the feasibility of the system and sorting algorithm.

关键词： Cascaded H-bridge AC split battery balancing current controller sorting algorithm

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Mahalanobis Distance and Maximum Likelihood Based Classification for Identifying Tobacco in Pakistan 7

Mahalanobis Distance and Maximum Likelihood Based Classifica...

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7th International Conference on Recent Advances in Space Technologies (RAST)

作者： Ahmed, Aziz Muaz, Muhammad Ali, Manzoor Yasir, Muhammad Ullah, Sadiq Khan, Shahbaz Univ Engn & Technol Dept Telecommun Engn Mardan Campus Peshawar Pakistan

ISBN: (纸本)9781479976973

Classifying cash crops through satellite based remote sensing has proved to be effective for reliable ground based agricultural statistics. In this study, frequently used simple and fast classification algorithms i.e., Mahalanobis Distance and Maximum Likelihood Classification (MLC) are compared for classifying tobacco crops by the end of June in north-western Pakistan. High Geometric Resolution imagery of SPOT-5 (2.5m) is used as the base image for comparison over a large pilot region. Our results indicate that MLC is more accurate than its simple form Mahalanobis distance with overall accuracy of 93.91% and kappa coefficient of 0.9181. Though it is visually seen that MLC has over-estimated tobacco crops in the unclassified region but this effect is mitigated with the help of two additional classes namely 'interfering separation' and 'interfering settlements'. It is recommended to use and compare MLC for future detection of tobacco crops in north-western Pakistan.

关键词： microprocessor logic circuit MLC1 gene Pakistan maximum likelihood Tobacco Products crops agricultural statistics sorting algorithm cash crop based

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Non-Homogeneous Hidden Markov Chain Models for Wavelet-Based Hyperspectral Image Processing

Non-Homogeneous Hidden Markov Chain Models for Wavelet-Based...

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51st IEEE Annual Allerton Conference on Communication, Control, and Computing

作者： Duarte, Marco F. Parente, Mario Univ Massachusetts Dept Elect & Comp Engn Amherst MA 01003 USA

ISBN: (纸本)9781479934096

We consider the use of non-homogeneous Markov chain (NHMC) models for wavelet transformations of hyper-spectral signatures to generate features for signal processing purposes. Inspired by the use of hidden Markov trees for natural images, the NHMC model enables the characterization of absorption bands and other structural features of mineral spectra that are used by experts in tasks like classification and unmixing, primarily in an ad-hoc fashion. We show that NHMC models can successfully identify and capture the information in a spectral signature dataset that can be exploited by standard classification algorithms to identify and differentiate spectral families. We also identify several metrics that can help determine whether each spectral band is informative to classification in a multiscale fashion.

关键词： Hidden Markov models Markov chain hyperspectral imagery spectral bands Absorption bands signal processing Metronidazole Professional personnel Image processing Religious Missions Spectrum signatures isostructuralism sorting algorithm

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FCI: Feature Cross and User Interest Network 1

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10th CCF Big Data Conference (BigData)

作者： Lei, Dejun Southwest Petr Univ Sch Comp Sci 8 Xindu Ave Chengdu 610599 Sichuan Peoples R China

ISBN: (数字)9789811983313

ISBN: (纸本)9789811983306;9789811983313

Recommendation systems are widely used on Internet platforms and the Recommendation system is one of the most mature scenarios for data mining applications. Ranking algorithms in recommender systems are the most effective means to increase user clicks. At present, the recommendation system ranking algorithm is mainly divided into two categories. One is based on data mining, such as user features, product features, and scene features and crosses these functions manually or automatically. The second method, by mining the user's behavior sequence, obtains the user's interests and displays the product to the user. The first approach does not mine useful behavioral data. The second method cannot effectively perform feature crossover and loses some crossover information between users and products. This paper proposes a new ranking method for recommender systems. Feature Cross and User Interest Network FCI. It can efficiently and automatically discover cross features based on users, products, and scenarios. At the same time, mining the historical behavior information of users. In this algorithm, firstly our put-forward model resembles a wide-depth structure. Wide structure puts feature intersection network, deep structure puts user historical behavior mining network. Secondly experimental comparisons are made by changing different feature intersection networks and user behavior sequence networks. Finally, by adding the pre-training vector of the product, compare different pre-training methods. This approach greatly improves the CTR in practical recommender systems.

关键词： Recommended system Behavior mining Feature-cross sorting algorithm Recommendation model

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Intellectual Scaling in a Distributed Cloud Application Architecture: a Message Classification algorithm

Intellectual Scaling in a Distributed Cloud Application Arch...

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2015 International Conference "Stability and Control Processes" in Memory of V.I. Zubov (SCP)

作者： Iakushkin, Oleg St Petersburg State Univ 7-9 Univ Skaya Nab St Petersburg 199034 Russia

ISBN: (纸本)9781467376983

The service systems deployed in a cloud environment have a volatile business logic which cannot be fully described by messaging patterns now available. Firstly, the work of distributed service systems is heavily influenced by the type, format, topic, and content of messages. Secondly, the existing middleware solutions for message exchange have a very narrow functionality focused exclusively on message passing between the nodes of a distributed system. They pay no attention to the features of the messages sent. However, scaling in hybrid and geo-distributed cloud solutions requires a more comprehensive approach. So does the analysis of the state of system modules. This paper offers an algorithm allowing to classify messages which are sent via the same protocol but have various content and do not correspond to a pre-set format. We provide an example of using such algorithm in middleware architecture. The major advantages and drawbacks of the algorithm are described with regard to a distributed cloud system.

关键词： Messages CLOUDS Clouds program architecture information exchange sorting algorithm water service reliability Distributed Systems message passing Scale formation Middleware intellectuals

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A Target Classification algorithm Based on Transportation Sensing Network

A Target Classification Algorithm Based on Transportation Se...

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Workshop on Power Electronics and Intelligent Transportation System

作者： Cui Xun-xue Qiu Guo-xin Zeng Jian-qin Xing Li-jun Liu Qi New Star Res Inst Appl Technol Hefei 230031 Peoples R China

ISBN: (纸本)9780769533421

Target classification is an important enabling technology for the monitoring task in transportation sensing networks. In the paper the magnetic signal and seismic acceleration signal are collected, analyzed and transmitted for a mobile road target. A classification algorithm based on the sensor network is proposed, which adopts a peak and valley pattern of hybrid detection signals from different sensors. The hardware equipment system of sensor node is devised. The terminal nodes are small with low power consumption so that the transportation sensing network is easy to deploy. The advantage of the algorithm lies on its sorting exactness of several kinds of targets. The results from many field tests have been shown that it is capable of identifying mobile targets on some roads in intelligent transportation system.

关键词： sorting algorithm field experimentation end node Sensor networks Targets transport Intelligent transportation systems Road low power consumption valleys TARGET CLASSIFICATION

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Emotions in speech -: Experiments with prosody and quality features in speech for use in categorical and dimensional emotion recognition environments

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International Conference on Natural Language Processing and Knowledge Engineering

作者： Borchert, M Düsterhöft, A Univ Business Technol & Design Hsch Wismar Dept EE&CS D-23952 Wismar Germany

ISBN: (纸本)0780393619

This paper focuses on features in speech and classification algorithms for using them in emotion recognition software. We illustrate a new approach concentrated on analyzing speech quality features. The quality features are formants, spectral energy distribution in different frequency bands, harmonics-to-noise ratio (in different frequency bands) and irregularities (jitter, shimmer). Some papers 131, 141 show that there is a relationship between quality features and the valence axis. This paper deals with dimensional approach to classify emotions. Therefore, mainly quality features will be taken for the valence axis to classify emotions and mainly prosody features will be taken for the arousal axis. Because our experiments show that single emotion recognition rates are up to 90 percent and the recognition rates for speaker independent recognition is about 70% for all classification algorithm, it seems that quality features are more appropriate to differentiate emotions with the same arousal and different valence levels in a dimensional approach. A prototypical emotion recognition software is implemented which is actually, tested for analyzing the mood of customers in call centers.

关键词： call centres emotion recognition signal classification speech recognition call centers categorical emotion recognition dimensional emotion recognition software emotion classification algorithms harmonics-to-noise ratio prosody features speaker independen Call Centers emotion recognition Emotions signal classification Speech prosody sorting algorithm Frequency bands DIMENSIONAL Harmonic noise

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