On Statistical Pattern Recognition In Independent Component Analysis Mixture Modelling

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On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling

Addisson Salazar

Author : Addisson Salazar
Publisher : Springer Science & Business Media
Page : 200 pages
File Size : 44,7 Mb
Release : 2012-07-20
Category : Technology & Engineering
ISBN : 9783642307522

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On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling by Addisson Salazar Pdf

A natural evolution of statistical signal processing, in connection with the progressive increase in computational power, has been exploiting higher-order information. Thus, high-order spectral analysis and nonlinear adaptive filtering have received the attention of many researchers. One of the most successful techniques for non-linear processing of data with complex non-Gaussian distributions is the independent component analysis mixture modelling (ICAMM). This thesis defines a novel formalism for pattern recognition and classification based on ICAMM, which unifies a certain number of pattern recognition tasks allowing generalization. The versatile and powerful framework developed in this work can deal with data obtained from quite different areas, such as image processing, impact-echo testing, cultural heritage, hypnograms analysis, web-mining and might therefore be employed to solve many different real-world problems.

Independent Component Analysis

Stephen Roberts,Richard Everson

Author : Stephen Roberts,Richard Everson
Publisher : Cambridge University Press
Page : 358 pages
File Size : 51,9 Mb
Release : 2001-03
Category : Computers
ISBN : 0521792983

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Independent Component Analysis by Stephen Roberts,Richard Everson Pdf

Independent Component Analysis (ICA) has recently become an important tool for modelling and understanding empirical datasets. It is a method of separating out independent sources from linearly mixed data, and belongs to the class of general linear models. ICA provides a better decomposition than other well-known models such as principal component analysis. This self-contained book contains a structured series of edited papers by leading researchers in the field, including an extensive introduction to ICA. The major theoretical bases are reviewed from a modern perspective, current developments are surveyed and many case studies of applications are described in detail. The latter include biomedical examples, signal and image denoising and mobile communications. ICA is discussed in the framework of general linear models, but also in comparison with other paradigms such as neural network and graphical modelling methods. The book is ideal for researchers and graduate students in the field.

Independent Component Analysis (ICA)

Addisson Salazar,Luis Vergara

Author : Addisson Salazar,Luis Vergara
Publisher : Nova Science Publishers
Page : 0 pages
File Size : 46,7 Mb
Release : 2018
Category : Independent component analysis
ISBN : 1536139947

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Independent Component Analysis (ICA) by Addisson Salazar,Luis Vergara Pdf

Modern treatment of data requires powerful tools that allow the possible valuable contents of that data to be thoroughly understood and exploited. From the plethora of techniques proposed to achieve those objectives, the independent component analysis (ICA) has emerged as a flexible and efficient approach to model and characterize arbitrary data densities. Considering adequate data preprocessing, ICA can be implemented for any kind of data including imaging; biomedical signals; telecommunication data; and web data. In this framework, this book embraces a significant vision of ICA that presents innovative theoretical and practical approaches. ICA has been increasingly studied as a suitable method for many applications where available data describe complex geometries. Thus, this book aims to be an updated and advanced source of knowledge to solve real-world problems efficiently based on ICA. In contrast to classical time and frequency domain filtering, ICA has been proposed as a statistical filtering tool considering the observed data as mixtures of hidden non-Gaussian distributions called sources. Those sources extracted by ICA can be related with meaningful information about the origin of the data and for data detection/classification. Therefore, the successful of ICA has been widely demonstrated in challenging blind source separation (BSS), feature extraction, and pattern recognition tasks. The suitability of ICA for a given problem of data analysis can be posed from different perspectives considering the physical interpretation of the phenomenon under analysis: (i) Estimation of the probability density of multivariate data without physical meaning; (ii) learning of some bases (usually called activation functions), which are more or less connected to the actual behaviors that are implicit in the physical phenomenon; and (iii) to identify where sources are originated and how they mix before arriving to the sensors to provide a physical explanation of the linear mixture model. In any case, even though the complexity of the problem constrains a physical interpretation, ICA can be used as a general-purpose data mining technique. The chapters that compose this book are written by premier researchers that present enlightening discussions, convincing demonstrations, and guidelines for future directions of research. The contents of this book span biomedical signal processing, dynamic modeling, next generation wireless communication, and sound and ultrasound signal processing. It also includes comprehensive works based on the related ICA techniques known as bounded component analysis (BCA) and non-negative matrix factorization (NMF).

Statistical Pattern Recognition

Andrew R. Webb

Author : Andrew R. Webb
Publisher : John Wiley & Sons
Page : 516 pages
File Size : 54,8 Mb
Release : 2003-07-25
Category : Mathematics
ISBN : 9780470854785

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Statistical Pattern Recognition by Andrew R. Webb Pdf

Statistical pattern recognition is a very active area of study andresearch, which has seen many advances in recent years. New andemerging applications - such as data mining, web searching,multimedia data retrieval, face recognition, and cursivehandwriting recognition - require robust and efficient patternrecognition techniques. Statistical decision making and estimationare regarded as fundamental to the study of pattern recognition. Statistical Pattern Recognition, Second Edition has been fullyupdated with new methods, applications and references. It providesa comprehensive introduction to this vibrant area - with materialdrawn from engineering, statistics, computer science and the socialsciences - and covers many application areas, such as databasedesign, artificial neural networks, and decision supportsystems. * Provides a self-contained introduction to statistical patternrecognition. * Each technique described is illustrated by real examples. * Covers Bayesian methods, neural networks, support vectormachines, and unsupervised classification. * Each section concludes with a description of the applicationsthat have been addressed and with further developments of thetheory. * Includes background material on dissimilarity, parameterestimation, data, linear algebra and probability. * Features a variety of exercises, from 'open-book' questions tomore lengthy projects. The book is aimed primarily at senior undergraduate and graduatestudents studying statistical pattern recognition, patternprocessing, neural networks, and data mining, in both statisticsand engineering departments. It is also an excellent source ofreference for technical professionals working in advancedinformation development environments. For further information on the techniques and applicationsdiscussed in this book please visit ahref="http://www.statistical-pattern-recognition.net/"www.statistical-pattern-recognition.net/a

Image and Signal Processing

Alamin Mansouri,Fathallah Nouboud,Alain Chalifour,Driss Mammass,Jean Meunier,Abderrahim El Moataz

Author : Alamin Mansouri,Fathallah Nouboud,Alain Chalifour,Driss Mammass,Jean Meunier,Abderrahim El Moataz
Publisher : Springer
Page : 408 pages
File Size : 46,9 Mb
Release : 2016-05-06
Category : Computers
ISBN : 9783319336183

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Image and Signal Processing by Alamin Mansouri,Fathallah Nouboud,Alain Chalifour,Driss Mammass,Jean Meunier,Abderrahim El Moataz Pdf

This book constitutes the refereed proceedings of the 7th International Conference, ICISP 2016, held in May/June 2016 in Trois-Rivières, QC, Canada. The 40 revised full papers were carefully reviewed and selected from 83 submissions. The contributions are organized in topical sections on features extraction, computer vision, and pattern recognition; multispectral and color imaging; image filtering, segmentation, and super-resolution; signal processing; biomedical imaging; geoscience and remote sensing; watermarking, authentication and coding; and 3d acquisition, processing, and applications.

Advances in Computational Intelligence

Ignacio Rojas,Gonzalo Joya,Andreu Catala

Author : Ignacio Rojas,Gonzalo Joya,Andreu Catala
Publisher : Springer
Page : 761 pages
File Size : 40,5 Mb
Release : 2017-06-04
Category : Computers
ISBN : 9783319591537

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Advances in Computational Intelligence by Ignacio Rojas,Gonzalo Joya,Andreu Catala Pdf

This two-volume set LNCS 10305 and LNCS 10306 constitutes the refereed proceedings of the 14th International Work-Conference on Artificial Neural Networks, IWANN 2017, held in Cadiz, Spain, in June 2017. The 126 revised full papers presented in this double volume were carefully reviewed and selected from 199 submissions. The papers are organized in topical sections on Bio-inspired Computing; E-Health and Computational Biology; Human Computer Interaction; Image and Signal Processing; Mathematics for Neural Networks; Self-organizing Networks; Spiking Neurons; Artificial Neural Networks in Industry ANNI'17; Computational Intelligence Tools and Techniques for Biomedical Applications; Assistive Rehabilitation Technology; Computational Intelligence Methods for Time Series; Machine Learning Applied to Vision and Robotics; Human Activity Recognition for Health and Well-Being Applications; Software Testing and Intelligent Systems; Real World Applications of BCI Systems; Machine Learning in Imbalanced Domains; Surveillance and Rescue Systems and Algorithms for Unmanned Aerial Vehicles; End-User Development for Social Robotics; Artificial Intelligence and Games; and Supervised, Non-Supervised, Reinforcement and Statistical Algorithms.

Advances in Artificial Intelligence -- IBERAMIA 2004

Christian Lemaitre,Carlos A. Reyes,Jesus A. Gonzalez

Author : Christian Lemaitre,Carlos A. Reyes,Jesus A. Gonzalez
Publisher : Springer
Page : 990 pages
File Size : 40,5 Mb
Release : 2004-11-03
Category : Computers
ISBN : 9783540304982

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Advances in Artificial Intelligence -- IBERAMIA 2004 by Christian Lemaitre,Carlos A. Reyes,Jesus A. Gonzalez Pdf

This book constitutes the refereed proceedings of the 9th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2004, held in Puebla, Mexico in November 2004. The 97 revised full papers presented were carefully reviewed and selected from 304 submissions. The papers are organized in topical sections on distributed AI and multi-agent systems, knowledge engineering and case-based reasoning, planning and scheduling, machine learning and knowledge acquisition, natural language processing, knowledge representation and reasoning, knowledge discovery and data mining, robotics, computer vision, uncertainty and fuzzy systems, genetic algorithms and neural networks, AI in education, and miscellaneous topics.

Structural, Syntactic, and Statistical Pattern Recognition

International Association for Pattern Recognition

Author : International Association for Pattern Recognition
Publisher : Springer Science & Business Media
Page : 884 pages
File Size : 48,9 Mb
Release : 2002-07-24
Category : Computers
ISBN : 9783540440116

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Structural, Syntactic, and Statistical Pattern Recognition by International Association for Pattern Recognition Pdf

This book constitutes the refereed proceedings of the 9th International Workshop on Structural and Syntctic Pattern Recognition, SSPR 2002 and the 4th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2002 held jointly in Windsor, Ontario, Canada in August 2002. The 45 revised full papers and 35 poster papers presented together with three invited papers were carefully reviewed and selected from 116 submissions. The papers are organized in topical sections on graphs, grammars, and languages; graphs, strings, and grammars; documents and OCR; image shape analysis and application; density estimation and distribution models; multi classifiers and fusion; feature extraction and selection; general methodology; and image shape analysis and application.

Encyclopedia of Information Science and Technology, Fourth Edition

Khosrow-Pour, D.B.A., Mehdi

Author : Khosrow-Pour, D.B.A., Mehdi
Publisher : IGI Global
Page : 8104 pages
File Size : 45,8 Mb
Release : 2017-06-20
Category : Computers
ISBN : 9781522522560

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Encyclopedia of Information Science and Technology, Fourth Edition by Khosrow-Pour, D.B.A., Mehdi Pdf

In recent years, our world has experienced a profound shift and progression in available computing and knowledge sharing innovations. These emerging advancements have developed at a rapid pace, disseminating into and affecting numerous aspects of contemporary society. This has created a pivotal need for an innovative compendium encompassing the latest trends, concepts, and issues surrounding this relevant discipline area. During the past 15 years, the Encyclopedia of Information Science and Technology has become recognized as one of the landmark sources of the latest knowledge and discoveries in this discipline. The Encyclopedia of Information Science and Technology, Fourth Edition is a 10-volume set which includes 705 original and previously unpublished research articles covering a full range of perspectives, applications, and techniques contributed by thousands of experts and researchers from around the globe. This authoritative encyclopedia is an all-encompassing, well-established reference source that is ideally designed to disseminate the most forward-thinking and diverse research findings. With critical perspectives on the impact of information science management and new technologies in modern settings, including but not limited to computer science, education, healthcare, government, engineering, business, and natural and physical sciences, it is a pivotal and relevant source of knowledge that will benefit every professional within the field of information science and technology and is an invaluable addition to every academic and corporate library.

Advanced Methodologies and Technologies in System Security, Information Privacy, and Forensics

Khosrow-Pour, D.B.A., Mehdi

Author : Khosrow-Pour, D.B.A., Mehdi
Publisher : IGI Global
Page : 417 pages
File Size : 50,6 Mb
Release : 2018-10-05
Category : Computers
ISBN : 9781522574934

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Advanced Methodologies and Technologies in System Security, Information Privacy, and Forensics by Khosrow-Pour, D.B.A., Mehdi Pdf

Cyber-attacks are rapidly becoming one of the most prevalent issues globally, and as they continue to escalate, it is imperative to explore new approaches and technologies that help ensure the security of the online community. Beyond cyber-attacks, personal information is now routinely and exclusively housed in cloud-based systems. The rising use of information technologies requires stronger information security and system procedures to reduce the risk of information breaches. Advanced Methodologies and Technologies in System Security, Information Privacy, and Forensics presents emerging research and methods on preventing information breaches and further securing system networks. While highlighting the rising concerns in information privacy and system security, this book explores the cutting-edge methods combatting digital risks and cyber threats. This book is an important resource for information technology professionals, cybercrime researchers, network analysts, government agencies, business professionals, academicians, and practitioners seeking the most up-to-date information and methodologies on cybercrime, digital terrorism, network security, and information technology ethics.

Computational Science – ICCS 2019

João M. F. Rodrigues,Pedro J. S. Cardoso,Jânio Monteiro,Roberto Lam,Valeria V. Krzhizhanovskaya,Michael H. Lees,Jack J. Dongarra,Peter M.A. Sloot

Author : João M. F. Rodrigues,Pedro J. S. Cardoso,Jânio Monteiro,Roberto Lam,Valeria V. Krzhizhanovskaya,Michael H. Lees,Jack J. Dongarra,Peter M.A. Sloot
Publisher : Springer
Page : 744 pages
File Size : 48,7 Mb
Release : 2019-06-07
Category : Computers
ISBN : 9783030227449

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Computational Science – ICCS 2019 by João M. F. Rodrigues,Pedro J. S. Cardoso,Jânio Monteiro,Roberto Lam,Valeria V. Krzhizhanovskaya,Michael H. Lees,Jack J. Dongarra,Peter M.A. Sloot Pdf

The five-volume set LNCS 11536, 11537, 11538, 11539 and 11540 constitutes the proceedings of the 19th International Conference on Computational Science, ICCS 2019, held in Faro, Portugal, in June 2019. The total of 65 full papers and 168 workshop papers presented in this book set were carefully reviewed and selected from 573 submissions (228 submissions to the main track and 345 submissions to the workshops). The papers were organized in topical sections named: Part I: ICCS Main Track Part II: ICCS Main Track; Track of Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Track of Agent-Based Simulations, Adaptive Algorithms and Solvers; Track of Applications of Matrix Methods in Artificial Intelligence and Machine Learning; Track of Architecture, Languages, Compilation and Hardware Support for Emerging and Heterogeneous Systems Part III: Track of Biomedical and Bioinformatics Challenges for Computer Science; Track of Classifier Learning from Difficult Data; Track of Computational Finance and Business Intelligence; Track of Computational Optimization, Modelling and Simulation; Track of Computational Science in IoT and Smart Systems Part IV: Track of Data-Driven Computational Sciences; Track of Machine Learning and Data Assimilation for Dynamical Systems; Track of Marine Computing in the Interconnected World for the Benefit of the Society; Track of Multiscale Modelling and Simulation; Track of Simulations of Flow and Transport: Modeling, Algorithms and Computation Part V: Track of Smart Systems: Computer Vision, Sensor Networks and Machine Learning; Track of Solving Problems with Uncertainties; Track of Teaching Computational Science; Poster Track ICCS 2019 Chapter “Comparing Domain-decomposition Methods for the Parallelization of Distributed Land Surface Models” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Advances in Computer Vision and Computational Biology

Hamid R. Arabnia,Leonidas Deligiannidis,Hayaru Shouno,Fernando G. Tinetti,Quoc-Nam Tran

Author : Hamid R. Arabnia,Leonidas Deligiannidis,Hayaru Shouno,Fernando G. Tinetti,Quoc-Nam Tran
Publisher : Springer Nature
Page : 903 pages
File Size : 54,7 Mb
Release : 2021-08-05
Category : Technology & Engineering
ISBN : 9783030710514

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Advances in Computer Vision and Computational Biology by Hamid R. Arabnia,Leonidas Deligiannidis,Hayaru Shouno,Fernando G. Tinetti,Quoc-Nam Tran Pdf

The book presents the proceedings of four conferences: The 24th International Conference on Image Processing, Computer Vision, & Pattern Recognition (IPCV'20), The 6th International Conference on Health Informatics and Medical Systems (HIMS'20), The 21st International Conference on Bioinformatics & Computational Biology (BIOCOMP'20), and The 6th International Conference on Biomedical Engineering and Sciences (BIOENG'20). The conferences took place in Las Vegas, NV, USA, July 27-30, 2020, and are part of the larger 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), which features 20 major tracks. Authors include academics, researchers, professionals, and students. Presents the proceedings of four conferences as part of the 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20); Includes the tracks on Image Processing, Computer Vision, & Pattern Recognition, Health Informatics & Medical Systems, Bioinformatics, Computational Biology & Biomedical Engineering; Features papers from IPCV'20, HIMS'20, BIOCOMP'20, and BIOENG'20.

Clays, Clay Minerals and Ceramic Materials Based on Clay Minerals

Gustavo Morari Do Nascimento

Author : Gustavo Morari Do Nascimento
Publisher : BoD – Books on Demand
Page : 196 pages
File Size : 51,6 Mb
Release : 2016-03-09
Category : Science
ISBN : 9789535122593

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Clays, Clay Minerals and Ceramic Materials Based on Clay Minerals by Gustavo Morari Do Nascimento Pdf

This book presents the state-of-the-art results of characterization of clays, clay minerals and ceramic materials based on clay minerals. The main goal of this work is to contribute to the rationalization of some important results obtained in the open area of clays and clay materials characterization. Moreover, this book also provides a comprehensive account on polymer and biopolymer-clay nanocomposites, use of clay as adsorption materials for industrial pollutants, ceramic materials in cultural heritage and physical-chemistry aspects of clay and clay minerals aqueous dispersions. This book will be beneficial for students, teachers and researchers of many areas who are interested to expand their knowledge about clays and its derivates in the fields of Nanotechnology, Biotechnology, Environmental Science, Industrial Remediation, Cultural Heritage, etc.

Independent Component Analysis

Aapo Hyvärinen,Juha Karhunen,Erkki Oja

Author : Aapo Hyvärinen,Juha Karhunen,Erkki Oja
Publisher : John Wiley & Sons
Page : 505 pages
File Size : 45,5 Mb
Release : 2004-04-05
Category : Science
ISBN : 9780471464198

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Independent Component Analysis by Aapo Hyvärinen,Juha Karhunen,Erkki Oja Pdf

A comprehensive introduction to ICA for students and practitioners Independent Component Analysis (ICA) is one of the most exciting new topics in fields such as neural networks, advanced statistics, and signal processing. This is the first book to provide a comprehensive introduction to this new technique complete with the fundamental mathematical background needed to understand and utilize it. It offers a general overview of the basics of ICA, important solutions and algorithms, and in-depth coverage of new applications in image processing, telecommunications, audio signal processing, and more. Independent Component Analysis is divided into four sections that cover: * General mathematical concepts utilized in the book * The basic ICA model and its solution * Various extensions of the basic ICA model * Real-world applications for ICA models Authors Hyvarinen, Karhunen, and Oja are well known for their contributions to the development of ICA and here cover all the relevant theory, new algorithms, and applications in various fields. Researchers, students, and practitioners from a variety of disciplines will find this accessible volume both helpful and informative.

Statistical Pattern Recognition

Andrew R. Webb,Keith D. Copsey

Author : Andrew R. Webb,Keith D. Copsey
Publisher : John Wiley & Sons
Page : 604 pages
File Size : 50,9 Mb
Release : 2011-10-13
Category : Mathematics
ISBN : 9781119961406

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Statistical Pattern Recognition by Andrew R. Webb,Keith D. Copsey Pdf

Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions. It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields, including the areas of engineering, statistics, computer science and the social sciences. The book has been updated to cover new methods and applications, and includes a wide range of techniques such as Bayesian methods, neural networks, support vector machines, feature selection and feature reduction techniques.Technical descriptions and motivations are provided, and the techniques are illustrated using real examples. Statistical Pattern Recognition, 3rd Edition: Provides a self-contained introduction to statistical pattern recognition. Includes new material presenting the analysis of complex networks. Introduces readers to methods for Bayesian density estimation. Presents descriptions of new applications in biometrics, security, finance and condition monitoring. Provides descriptions and guidance for implementing techniques, which will be invaluable to software engineers and developers seeking to develop real applications Describes mathematically the range of statistical pattern recognition techniques. Presents a variety of exercises including more extensive computer projects. The in-depth technical descriptions make the book suitable for senior undergraduate and graduate students in statistics, computer science and engineering. Statistical Pattern Recognition is also an excellent reference source for technical professionals. Chapters have been arranged to facilitate implementation of the techniques by software engineers and developers in non-statistical engineering fields. www.wiley.com/go/statistical_pattern_recognition

On Statistical Pattern Recognition In Independent Component Analysis Mixture Modelling

On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling by Addisson Salazar Pdf

Independent Component Analysis by Stephen Roberts,Richard Everson Pdf

Independent Component Analysis (ICA) by Addisson Salazar,Luis Vergara Pdf

Statistical Pattern Recognition by Andrew R. Webb Pdf

Image and Signal Processing by Alamin Mansouri,Fathallah Nouboud,Alain Chalifour,Driss Mammass,Jean Meunier,Abderrahim El Moataz Pdf

Advances in Computational Intelligence by Ignacio Rojas,Gonzalo Joya,Andreu Catala Pdf

Advances in Artificial Intelligence -- IBERAMIA 2004 by Christian Lemaitre,Carlos A. Reyes,Jesus A. Gonzalez Pdf

Structural, Syntactic, and Statistical Pattern Recognition by International Association for Pattern Recognition Pdf

Encyclopedia of Information Science and Technology, Fourth Edition by Khosrow-Pour, D.B.A., Mehdi Pdf

Advanced Methodologies and Technologies in System Security, Information Privacy, and Forensics by Khosrow-Pour, D.B.A., Mehdi Pdf

Computational Science – ICCS 2019 by João M. F. Rodrigues,Pedro J. S. Cardoso,Jânio Monteiro,Roberto Lam,Valeria V. Krzhizhanovskaya,Michael H. Lees,Jack J. Dongarra,Peter M.A. Sloot Pdf

Advances in Computer Vision and Computational Biology by Hamid R. Arabnia,Leonidas Deligiannidis,Hayaru Shouno,Fernando G. Tinetti,Quoc-Nam Tran Pdf

Clays, Clay Minerals and Ceramic Materials Based on Clay Minerals by Gustavo Morari Do Nascimento Pdf

Independent Component Analysis by Aapo Hyvärinen,Juha Karhunen,Erkki Oja Pdf

Statistical Pattern Recognition by Andrew R. Webb,Keith D. Copsey Pdf

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