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On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling

component analysis mixture modelling (ICAMM). This thesis defines a novel formalism for pattern recognition and classification based on ICAMM, which;

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Mixture Modelling for Medical and Health Sciences

typical daily problems to complex data modelling. Emphasis on the use of a wide variety of component densities for statistical modelling;

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Mixture Modelling for Medical and Health Sciences

extensively on his research interests, which include cluster analysis, pattern recognition, random-effects modelling, and survival analysis;

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Advances in Independent Component Analysis and Learning Machines

of independent component analysis, and its influence in important areas such as statistical signal processing, pattern recognition and deep learning

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Structural, Syntactic, and Statistical Pattern Recognition

This book constitutes the proceedings of the Joint IAPR International Workshop on Structural Syntactic, and Statistical Pattern Recognition;

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Pattern Recognition in Nanoscience, Environmental Engineering & Archeology

This book presents new and important research on pattern recognition -- the research area that studies the operation and design of systems;

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Finite Mixture Models

analysis and other areas such as unsupervised pattern recognition, speech recognition, and medical imaging, the book describes the formulations;

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Pattern Recognition

discriminant analysis, feature extraction, error estimation, cluster analysis (together sometimes called statistical pattern recognition), grammatical;

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Handbook Of Pattern Recognition And Computer Vision (3rd Edition)

in the field. On the basic methods in pattern recognition and computer vision, topics range from statistical pattern recognition to array;

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Pattern Recognition in Biology

subdisciplines like discriminant analysis, feature extraction, error estimation, cluster analysis (together sometimes called statistical pattern;

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Introduction to Statistical Pattern Recognition

This completely revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a;

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Structural, Syntactic, and Statistical Pattern Recognition

This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern;

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Progress in Chemometrics Research

in multivariate calibration, pattern recognition, classification and discriminant analysis, multivariate modelling, and monitoring of processes. The main;

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Pattern Recognition

learning and pattern recognition; mathematical foundations, statistical data analysis and models; motion and segmentation; pose, face and gesture;

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Statistical Pattern Recognition

Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract;

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Statistical Pattern Recognition

Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract;

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Pattern Recognition

This book constitutes the refereed proceedings of the 35th German Conference on Pattern Recognition, GCPR 2013, held in Saarbrücken;

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Applications of Pattern Recognition

include the application of pattern recognition to seismic wave interpretation, to system reliability problems, to medical data analysis, as well;

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Data Analysis in Vegetation Ecology

The 3rd edition of this popular textbook introduces the reader to the investigation of vegetation systems with an emphasis on data analysis;

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Perspectives on Pattern Recognition

, based on the extracted features. This book presents topical research in the study of pattern recognition, including pattern recognition;

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Netlab: Algorithms for Pattern Recognition

application of neural networks to pattern analysis problems. All parts of the toolbox interact in a coherent way, and implementations and descriptions;

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Seismic Modelling and Pattern Recognition in Oil Exploration

scientists are often confronted. The reader is introduced not only to the essentials of computer modelling, data analysis and pattern recognition;

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Progress in Pattern Recognition Image Analysis Computer Vision and Applicatio

This book constitutes the refereed proceedings of the 20th Iberoamerican Congress on Pattern Recognition, CIARP 2015, held in Montevideo;

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Pattern Recognition and Machine Vision

. It is probably true to say that most people are affected by, or use applications of pattern recognition in daily life. Today, on the eve;

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Handbook of Mixture Analysis

Mixture models have been around for over 150 years, and they are found in many branches of statistical modelling, as a versatile and;

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Neural Networks and Statistical Learning

radial basis function network; * recurrent neural networks; * nonnegative matrix factorization; * independent component analysis;

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Pattern Recognition

in topical sections on computer vision and image analysis; pattern recognition and artificial intelligent techniques; signal processing and analysis;

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