Central Library

Neural-based orthogonal data fitting : (Record no. 74124)

000 -LEADER
fixed length control field 06280nam a2200889 i 4500
001 - CONTROL NUMBER
control field 5732789
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220712205756.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 151221s2011 njua ob 001 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9780470638286
-- ebook
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
-- electronic
100 1# - AUTHOR NAME
Author Cirrincione, Giansalvo,
245 10 - TITLE STATEMENT
Title Neural-based orthogonal data fitting :
Sub Title the EXIN neural networks /
300 ## - PHYSICAL DESCRIPTION
Number of Pages 1 PDF (xviii, 243 pages, [12] pages) :
490 1# - SERIES STATEMENT
Series statement Adaptive and learning systems for signal processing, communications and control series ;
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Foreword -- Preface -- 1 The Total Least Squares Problems -- 1.1 Introduction -- 1.2 Some TLS Applications -- 1.3 Preliminaries -- 1.4 Ordinary Least Squares Problems -- 1.5 Basic TLS Problem -- 1.6 Multidimensional TLS Problem -- 1.7 Nongeneric Unidimensional TLS Problem -- 1.8 Mixed OLS-TLS Problem -- 1.9 Algebraic Comparisons Between TLS and OLS -- 1.10 Statistical Properties and Validity -- 1.11 Basic Data Least Squares Problem -- 1.12 The Partial TLS Algorithm -- 1.13 Iterative Computation Methods -- 1.14 Rayleigh Quotient Minimization Non Neural and Neural Methods -- 2 The MCA EXIN Neuron -- 2.1 The Rayleigh Quotient -- 2.2 The Minor Component Analysis -- 2.3 The MCA EXIN Linear Neuron -- 2.4 The Rayleigh Quotient Gradient Flows -- 2.5 The MCA EXIN ODE Stability Analysis -- 2.6 Dynamics of the MCA Neurons -- 2.7 Fluctuations (Dynamic Stability) and Learning Rate -- 2.8 Numerical Considerations -- 2.9 TLS Hyperplane Fitting -- 2.10 Simulations for the MCA EXIN Neuron -- 2.11 Conclusions -- 3 Variants of the MCA EXIN Neuron -- 3.1 High-Order MCA Neurons -- 3.2 The Robust MCA EXIN Nonlinear Neuron (NMCA EXIN) -- 3.3 Extensions of the Neural MCA -- 4 Introduction to the TLS EXIN Neuron -- 4.1 From MCA EXIN to TLS EXIN -- 4.2 Deterministic Proof and Batch Mode -- 4.3 Acceleration Techniques -- 4.4 Comparison with TLS GAO -- 4.5 A TLS Application: Adaptive IIR Filtering -- 4.6 Numerical Considerations -- 4.7 The TLS Cost Landscape: Geometric Approach -- 4.8 First Considerations on the TLS Stability Analysis -- 5 Generalization of Linear Regression Problems -- 5.1 Introduction -- 5.2 The Generalized Total Least Squares (GeTLS EXIN) Approach -- 5.3 The GeTLS Stability Analysis -- 5.4 Neural Nongeneric Unidimensional TLS -- 5.5 Scheduling -- 5.6 The Accelerated MCA EXIN Neuron (MCA EXIN+) -- 5.7 Further Considerations -- 5.8 Simulations for the GeTLS EXIN Neuron -- 6 The GeMCA EXIN Theory -- 6.1 The GeMCA Approach -- 6.2 Analysis of Matrix K -- 6.3 Analysis of the Derivative of the Eigensystem of GeTLS EXIN.
505 8# - FORMATTED CONTENTS NOTE
Remark 2 6.4 Rank One Analysis Around the TLS Solution -- 6.5 The GeMCA Spectra -- 6.6 Qualitative Analysis of the Critical Points of the GeMCA EXIN Error Function -- 6.7 Conclusion -- References -- Index.
520 ## - SUMMARY, ETC.
Summary, etc "Written by three leaders in the field of neural based algorithms, Neural Based Orthogonal Data Fitting proposes several neural networks, all endowed with a complete theory which not only explains their behavior, but also compares them with the existing neural and traditional algorithms. The algorithms are studied from different points of view, including: as a differential geometry problem, as a dynamic problem, as a stochastic problem, and as a numerical problem. All algorithms have also been analyzed on real time problems (large dimensional data matrices) and have shown accurate solutions. Where most books on the subject are dedicated to PCA (principal component analysis) and consider MCA (minor component analysis) as simply a consequence, this is the fist book to start from the MCA problem and arrive at important conclusions about the PCA problem."--
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
Subject Neural networks (Computer science)
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
Subject Numerical analysis.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
Subject Orthogonalization methods.
700 1# - AUTHOR 2
Author 2 Cirrincione, Maurizio,
856 42 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=5732789
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Hoboken, New Jersey :
-- Wiley,
-- c2010.
264 #2 -
-- [Piscataqay, New Jersey] :
-- IEEE Xplore,
-- [2011]
336 ## -
-- text
-- rdacontent
337 ## -
-- electronic
-- isbdmedia
338 ## -
-- online resource
-- rdacarrier
520 ## - SUMMARY, ETC.
-- Provided by publisher.
588 ## -
-- Description based on PDF viewed 12/21/2015.
695 ## -
-- Acceleration
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-- Accuracy
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-- Adaptive systems
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-- Approximation methods
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-- Artificial intelligence
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-- Bibliographies
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-- Biological neural networks
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-- Biomedical measurements
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-- Correlation
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-- Cost function
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-- Eigenvalues and eigenfunctions
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-- Equations
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-- GeMCA EXIN theory and generalized Rayleigh quotient
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-- GeMCA spectra
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-- Hebbian theory
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-- Indexes
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-- Learning systems
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-- Linear regression
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-- Logistics
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-- Mathematical model
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-- Neurons
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-- Noise
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-- Optical distortion
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-- Prediction algorithms
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-- Principal component analysis
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-- Robustness
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-- Signal processing
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-- Signal processing algorithms
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-- Training
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-- Vectors
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-- analysis of derivative of eigensystem of GeTLS EXIN

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