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Different Subspace Classification

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Krylov Subspace Methods with Application in Incompressible Fluid Flow Solvers

systems of equations with different types of matrices. Written in the simplest language possible and eliminating ambiguities, the text is easy;

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ModelBased Processing

including state estimation, tracking, detection, classification, controls, communications, and other applications that require reliable models that;

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Speech Enhancement

treated as different classes of methods and have been introduced in somewhat different contexts. Linear filtering methods originate in stochastic;

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Krylov Subspace Methods

The mathematical theory of Krylov subspace methods with a focus on solving systems of linear algebra;...

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Subspace Methods for System Identification

An in-depth introduction to subspace methods for system identification in discrete-time linear syste;...

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Narrowband Direction of Arrival Estimation for Antenna Arrays

This book provides an introduction to narrowband array signal processing, classical and subspace-bas;...

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Subspace . FUNKER VOGT, CD

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Aika . Subspace Radio, CD

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Hyperspectral Imaging

Hyperspectral Imaging: Techniques for Spectral Detection and Classification is an outgrowth of the research conducted over the years in the;

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Condition Monitoring with Vibration Signals

various feature extraction, feature selection, and classification methods as well as their applications to machine vibration datasets. It also;

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Narrowband Direction of Arrival Estimation for Antenna Arrays

This book provides an introduction to narrowband array signal processing, classical and subspace-bas;...

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Network Coding and Subspace Designs

This book, written by experts from universities and major research laboratories, addresses the hot t;...

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Machine Intelligence: Recent Advances

preserving data mining, as well as an authentication mechanism using fingerprint classification. Section V contains an extension of open source iCub;

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Robust Representation for Data Analytics

data analytics tasks, such as clustering, classification, time series modeling, outlier detection, collaborative filtering, community detection;

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Modern Approaches to the Invariant-Subspace Problem

One of the major unsolved problems in operator theory is the fifty-year-old invariant subspace probl;...

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Genetic Programming for Image Classification

accuracy and/or computational efficiency of GP for image classification. The proposed methods are applied to many different image classification;

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Genetic Programming for Image Classification

accuracy and/or computational efficiency of GP for image classification. The proposed methods are applied to many different image classification;

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Essential Classification

classification. It deals with fundamental questions as to the purpose of classification in different situations, and the needs and expectations of end;

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The Pocket Guide to Lymphoma Classification

The classification of lymphomas is a real headache: lymphomas often go by different names in different publications, and while some;

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International Classification of Procedures in Medicine

This 2-volume classification is intended to present in a systematic fashion the many procedures used in different branches of medicine, a;

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Landcover Classification and Topography

Mapper data (TM) to test the effect of topography on landcover classification for two different landcover classification legends.;

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Language and Classification

This volume adopts a practice-based approach to examine the different ways in which classification is communicated and negotiated;

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Language and Classification

This volume adopts a practice-based approach to examine the different ways in which classification is communicated and negotiated;

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The Standard Occupational Classification (SOC) 2010 Vol 3

and conventions underlying Standard Occupational Classification (SOC) which lists different groups, job tasks and the common job titles.;

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Algorithms for Regression and Classification

The focus of this dissertation is on robust regression and classification in genetic association studies. In the context of robust;

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New Classification Method Based on Modular Neural Networks with the LVQ Algorith

In this book a new model for data classification was developed. This new model is based on the competitive neural network Learning Vector;

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