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A first course in applied mathematics / / Jorge Rebaza
A first course in applied mathematics / / Jorge Rebaza
Autore Rebaza Jorge
Pubbl/distr/stampa Hoboken, NJ, : Wiley, 2012
Descrizione fisica 1 online resource (458 p.)
Disciplina 510
519
Soggetto topico Mathematical models
Computer simulation
ISBN 1-280-59248-6
9786613622310
1-118-27717-1
1-118-27715-5
1-118-27718-X
Classificazione MAT003000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto A First Course in Applied Mathematics; CONTENTS; Preface; 1 Basics of Linear Algebra; 1.1 Notation and Terminology; 1.2 Vector and Matrix Norms; 1.3 Dot Product and Orthogonality; 1.4 Special Matrices; 1.4.1 Diagonal and triangular matrices; 1.4.2 Hessenberg matrices; 1.4.3 Nonsingular and inverse matrices; 1.4.4 Symmetric and positive definite matrices; 1.4.5 Matrix exponential; 1.4.6 Permutation matrices; 1.4.7 Orthogonal matrices; 1.5 Vector Spaces; 1.6 Linear Independence and Basis; 1.7 Orthogonalization and Direct Sums; 1.8 Column Space, Row Space, and Null Space
1.8.1 Linear transformations1.9 Orthogonal Projections; 1.10 Eigenvalues and Eigenvectors; 1.11 Similarity; 1.12 Bezier Curves and Postscript Fonts; 1.12.1 Properties of Bezier curves; 1.12.2 Composite Bezier curves; 1.13 Final Remarks and Further Reading; Exercises; 2 Ranking Web Pages; 2.1 The Power Method; 2.2 Stochastic, Irreducible, and Primitive Matrices; 2.3 Google's PageRank Algorithm; 2.3.1 The personalization vector; 2.3.2 Speed of convergence and sparsity; 2.3.3 Power method and reordering; 2.4 Alternatives to the Power Method; 2.4.1 Linear system formulation
2.4.2 Iterative aggregation/disaggregation (IAD)2.4.3 IAD and linear systems; 2.5 Final Remarks and Further Reading; Exercises; 3 Matrix Factorizations; 3.1 LU Factorization; 3.1.1 The complex case; 3.1.2 Solving several systems; 3.1.3 The PA = LU factorization; 3.2 QR Factorization; 3.2.1 QR and Gram-Schmidt; 3.2.2 The complex case; 3.2.3 QR and similarity; 3.2.4 The QR algorithm; 3.2.5 QR and LU; 3.3 Singular Value Decomposition (SVD); 3.3.1 The complex case; 3.3.2 Low-rank approximations; 3.3.3 SVD and spectral norm; 3.4 Schur Factorization; 3.4.1 The complex case
3.4.2 Schur factorization and invariant subspaces3.4.3 Exchanging eigenblocks; 3.4.4 Block diagonalization; 3.5 Information Retrieval; 3.5.1 Query matching; 3.5.2 Low-rank query matching; 3.5.3 Term-term comparison; 3.6 Partition of Simple Substitution Cryptograms; 3.6.1 Rank-1 approximation; 3.6.2 Rank-2 approximation; 3.7 Final Remarks and Further Reading; Exercises; 4 Least Squares; 4.1 Projections and Normal Equations; 4.2 Least Squares and QR Factorization; 4.3 Lagrange Multipliers; 4.4 Final Remarks and Further Reading; Exercises; 5 Image Compression
5.1 Compressing with Discrete Cosine Transform5.1.1 1 -D discrete cosine transform; 5.1.2 2-D discrete cosine transform; 5.1.3 Image compression and the human visual system; 5.1.4 Basis functions and images; 5.1.5 Low-pass filtering; 5.1.6 Quantization; 5.1.7 Compression of color images; 5.2 Huffman Coding; 5.2.1 Huffman coding and JPEG; 5.3 Compression with SVD; 5.3.1 Compressing grayscale images; 5.3.2 Compressing color images; 5.4 Final Remarks and Further Reading; Exercises; 6 Ordinary Differential Equations; 6.1 One-Dimensional Differential Equations; 6.1.1 Existence and uniqueness
6.1.2 A simple population model
Record Nr. UNINA-9910830317403321
Rebaza Jorge  
Hoboken, NJ, : Wiley, 2012
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
A first course in applied mathematics / / Jorge Rebaza
A first course in applied mathematics / / Jorge Rebaza
Autore Rebaza Jorge
Pubbl/distr/stampa Hoboken, NJ, : Wiley, 2012
Descrizione fisica 1 online resource (458 p.)
Disciplina 510
519
Soggetto topico Mathematical models
Computer simulation
ISBN 1-280-59248-6
9786613622310
1-118-27717-1
1-118-27715-5
1-118-27718-X
Classificazione MAT003000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto A First Course in Applied Mathematics; CONTENTS; Preface; 1 Basics of Linear Algebra; 1.1 Notation and Terminology; 1.2 Vector and Matrix Norms; 1.3 Dot Product and Orthogonality; 1.4 Special Matrices; 1.4.1 Diagonal and triangular matrices; 1.4.2 Hessenberg matrices; 1.4.3 Nonsingular and inverse matrices; 1.4.4 Symmetric and positive definite matrices; 1.4.5 Matrix exponential; 1.4.6 Permutation matrices; 1.4.7 Orthogonal matrices; 1.5 Vector Spaces; 1.6 Linear Independence and Basis; 1.7 Orthogonalization and Direct Sums; 1.8 Column Space, Row Space, and Null Space
1.8.1 Linear transformations1.9 Orthogonal Projections; 1.10 Eigenvalues and Eigenvectors; 1.11 Similarity; 1.12 Bezier Curves and Postscript Fonts; 1.12.1 Properties of Bezier curves; 1.12.2 Composite Bezier curves; 1.13 Final Remarks and Further Reading; Exercises; 2 Ranking Web Pages; 2.1 The Power Method; 2.2 Stochastic, Irreducible, and Primitive Matrices; 2.3 Google's PageRank Algorithm; 2.3.1 The personalization vector; 2.3.2 Speed of convergence and sparsity; 2.3.3 Power method and reordering; 2.4 Alternatives to the Power Method; 2.4.1 Linear system formulation
2.4.2 Iterative aggregation/disaggregation (IAD)2.4.3 IAD and linear systems; 2.5 Final Remarks and Further Reading; Exercises; 3 Matrix Factorizations; 3.1 LU Factorization; 3.1.1 The complex case; 3.1.2 Solving several systems; 3.1.3 The PA = LU factorization; 3.2 QR Factorization; 3.2.1 QR and Gram-Schmidt; 3.2.2 The complex case; 3.2.3 QR and similarity; 3.2.4 The QR algorithm; 3.2.5 QR and LU; 3.3 Singular Value Decomposition (SVD); 3.3.1 The complex case; 3.3.2 Low-rank approximations; 3.3.3 SVD and spectral norm; 3.4 Schur Factorization; 3.4.1 The complex case
3.4.2 Schur factorization and invariant subspaces3.4.3 Exchanging eigenblocks; 3.4.4 Block diagonalization; 3.5 Information Retrieval; 3.5.1 Query matching; 3.5.2 Low-rank query matching; 3.5.3 Term-term comparison; 3.6 Partition of Simple Substitution Cryptograms; 3.6.1 Rank-1 approximation; 3.6.2 Rank-2 approximation; 3.7 Final Remarks and Further Reading; Exercises; 4 Least Squares; 4.1 Projections and Normal Equations; 4.2 Least Squares and QR Factorization; 4.3 Lagrange Multipliers; 4.4 Final Remarks and Further Reading; Exercises; 5 Image Compression
5.1 Compressing with Discrete Cosine Transform5.1.1 1 -D discrete cosine transform; 5.1.2 2-D discrete cosine transform; 5.1.3 Image compression and the human visual system; 5.1.4 Basis functions and images; 5.1.5 Low-pass filtering; 5.1.6 Quantization; 5.1.7 Compression of color images; 5.2 Huffman Coding; 5.2.1 Huffman coding and JPEG; 5.3 Compression with SVD; 5.3.1 Compressing grayscale images; 5.3.2 Compressing color images; 5.4 Final Remarks and Further Reading; Exercises; 6 Ordinary Differential Equations; 6.1 One-Dimensional Differential Equations; 6.1.1 Existence and uniqueness
6.1.2 A simple population model
Record Nr. UNINA-9910840611403321
Rebaza Jorge  
Hoboken, NJ, : Wiley, 2012
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Fourier transforms : principles and applications / / Eric W. Hansen
Fourier transforms : principles and applications / / Eric W. Hansen
Autore Hansen Eric W (Eric William), <1954->
Edizione [1st edition]
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley, , 2014
Descrizione fisica 1 online resource (774 p.)
Disciplina 515/.723
Soggetto topico Signal processing - Mathematical models
Image processing - Mathematical models
Fourier analysis
Soggetto genere / forma Electronic books.
ISBN 1-118-90169-X
Classificazione MAT003000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto FOURIER TRANSFORMS; Contents; Preface; Philosophy and Distinctives; Flow of the Book; Suggested Use; Acknowledgments; 1 Review of Prerequisite Mathematics; 1.1 Common notation; 1.2 Vectors in space; 1.3 Complex numbers; 1.4 Matrix algebra; 1.5 Mappings and functions; 1.6 Sinusoidal functions; 1.7 Complex exponentials; 1.8 Geometric series; 1.9 Results from calculus; 1.10 Top 10 ways to avoid errors in calculations; Problems; 2 Vector Spaces; 2.1 Signals and vector spaces; 2.2 Finite-dimensional vector spaces; 2.2.1 Norms and Metrics; 2.2.2 Inner Products
2.2.3 Orthogonal Expansion and Approximation2.3 Infinite-dimensional vector spaces; 2.3.1 Convergent Sequences; 2.3.3 Functions and the Lp Spaces; 2.4 Operators; 2.5 Creating orthonormal bases-the Gram-Schmidt process; 2.6 Summary; Problems; 3 The Discrete Fourier Transform; 3.1 Sinusoidal sequences; 3.2 The Discrete Fourier transform; 3.3 Interpreting the DFT; 3.4 DFT properties and theorems; 3.5 Fast Fourier transform; 3.6 Discrete cosine transform; 3.7 Summary; Problems; 4 The Fourier Series; 4.1 Sinusoids and physical systems; 4.2 Definitions and interpretation
4.3 Convergence of the Fourier series4.4 Fourier series properties and theorems; 4.5 The heat equation; 4.6 The vibrating string; 4.7 Antenna arrays; 4.8 Computing the Fourier series; 4.9 Discrete time Fourier transform; 4.9.1 Convergence Properties; 4.9.2 Theorems; 4.9.3 Discrete-time Systems; 4.9.4 Computing the DTFT; 4.10 Summary; Problems; 5 The Fourier Transform; 5.1 From Fourier series to Fourier transform; 5.2 Basic properties and some examples; 5.3 Fourier transform theorems; 5.4 Interpreting the Fourier transform; 5.5 Convolution; 5.5.1 Definition and basic properties
5.5.2 Convolution and Linear Systems5.5.3 Correlation; 5.6 More about the Fourier transform; 5.6.1 Fourier inversion in L1; 5.6.2 Fourier Transform in L2; 5.6.3 More about convolution; 5.7 Time-bandwidth relationships; 5.8 Computing the Fourier transform; 5.9 Time-frequency transforms; 5.10 Summary; Problems; 6 Generalized Functions; 6.1 Impulsive signals and spectra; 6.2 The delta function in a nutshell; 6.3 Generalized functions; 6.3.1 Functions and Generalized Functions; 6.3.2 Generalized Functions as Sequences of Functions; 6.3.3 Calculus of Generalized Functions
6.4 Generalized Fourier transform6.4.1 Definition; 6.4.2 Fourier Theorems; 6.5 Sampling theory and Fourier series; 6.5.1 Fourier Series, Again; 6.5.2 Periodic Generalized Functions; 6.5.3 The Sampling Theorem; 6.5.4 Discrete-time Fourier Transform; 6.6 Unifying the Fourier family; 6.6.1 Basis Functions and Orthogonality Relationships; 6.6.2 Sampling and Replication; 6.7 Summary; Problems; 7 Complex Function Theory; 7.1 Complex functions and their visualization; 7.2 Differentiation; 7.3 Analytic functions; 7.4 exp z and functions derived from it; 7.5 log z and functions derived from it
7.5.1 The Logarithm Function
Record Nr. UNINA-9910459967803321
Hansen Eric W (Eric William), <1954->  
Hoboken, New Jersey : , : Wiley, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Leading for organisational change : building purpose, motivation and belonging / / Jennifer Emery
Leading for organisational change : building purpose, motivation and belonging / / Jennifer Emery
Autore Emery Jennifer <1977->
Edizione [1st edition]
Pubbl/distr/stampa Chichester, West Sussex, United Kingdom : , : Wiley, , 2019
Descrizione fisica 323 pages
Disciplina 658.4/06
Soggetto topico Organizational change
Employee motivation
Personnel management
ISBN 1-119-51798-2
1-119-51795-8
Classificazione MAT003000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Machine generated contents note: Foreword Preface Introduction PART ONE: Foundation 1 Once Upon A Time 2 The Angel in the Marble 3 Milk And Mushrooms 4 Telling Stories 5 Everything Must Change PART TWO: Story 6 Beginnings 7 Starting Out 8 Making it happen PART THREE: BECAUSE 9 Belonging 10 Evolution 11 Confidence 12 Agility 13 Understanding 14 Simplicity 15 Energy PART FOUR: Implications 16 The Bigger Picture 17 The Best Thing You Can Bring Is Heart Bibliography Acknowledgements About the Author.
Record Nr. UNINA-9910793463903321
Emery Jennifer <1977->  
Chichester, West Sussex, United Kingdom : , : Wiley, , 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Leading for organisational change : building purpose, motivation and belonging / / Jennifer Emery
Leading for organisational change : building purpose, motivation and belonging / / Jennifer Emery
Autore Emery Jennifer <1977->
Edizione [1st edition]
Pubbl/distr/stampa Chichester, West Sussex, United Kingdom : , : Wiley, , 2019
Descrizione fisica 323 pages
Disciplina 658.4/06
Soggetto topico Organizational change
Employee motivation
Personnel management
ISBN 1-119-51798-2
1-119-51795-8
Classificazione MAT003000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Machine generated contents note: Foreword Preface Introduction PART ONE: Foundation 1 Once Upon A Time 2 The Angel in the Marble 3 Milk And Mushrooms 4 Telling Stories 5 Everything Must Change PART TWO: Story 6 Beginnings 7 Starting Out 8 Making it happen PART THREE: BECAUSE 9 Belonging 10 Evolution 11 Confidence 12 Agility 13 Understanding 14 Simplicity 15 Energy PART FOUR: Implications 16 The Bigger Picture 17 The Best Thing You Can Bring Is Heart Bibliography Acknowledgements About the Author.
Record Nr. UNINA-9910816411103321
Emery Jennifer <1977->  
Chichester, West Sussex, United Kingdom : , : Wiley, , 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Natural element method for the simulation of structures and processes [[electronic resource] /] / Francisco Chinesta ... [et al.]
Natural element method for the simulation of structures and processes [[electronic resource] /] / Francisco Chinesta ... [et al.]
Autore Chinesta Francisco
Pubbl/distr/stampa London, : ISTE
Descrizione fisica 1 online resource (255 p.)
Disciplina 624.1/7015118
624.17015118
Altri autori (Persone) ChinestaFrancisco
Collana ISTE
Soggetto topico Materials - Mechanical properties - Mathematical models
Numerical analysis
Numbers, Natural
Soggetto genere / forma Electronic books.
ISBN 1-118-61690-1
1-299-31421-X
1-118-61668-5
Classificazione MAT003000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Natural Element Method for the Simulation of Structures and Processes; Title Page; Copyright Page; Table of Contents; Foreword; Acknowledgements; Chapter 1. Introduction; 1.1. SPH method; 1.2. RKPM method; 1.2.1. Conditions of reproduction; 1.2.2. Correction of the kernel; 1.2.3. Discrete form of the approximation; 1.3. MLS based approximations; 1.4. Final note; Chapter 2. Basics of the Natural Element Method; 2.1. Introduction; 2.2. Natural neighbor Galerkin methods; 2.2.1. Interpolation of natural neighbors; 2.2.2. Discretization
2.2.3. Properties of the interpolant based on natural neighbors2.3. Exact imposition of the essential boundary conditions; 2.3.1. Introduction to alpha shapes; 2.3.2. CNEM approaches; 2.4. Mixed approximations of natural neighbor type; 2.4.1. Considering the restriction of incompressibility; 2.4.2. Mixed approximations in the Galerkin method; 2.4.3. Natural neighbor partition of unity; 2.4.3.1. Partition of unity method; 2.4.3.2. Enrichment of the natural neighbor interpolants; 2.5. High order natural neighbor interpolants; 2.5.1. Hiyoshi-Sugihara interpolant
2.5.2. The De Boor algorithm for B-splines2.5.3. B-spline surfaces and natural neighboring; 2.5.3.1. Some definitions; 2.5.3.2. Surface properties; 2.5.3.3. The case of repeated nodes; Chapter 3. Numerical Aspects; 3.1. Searching for natural neighbors; 3.2. Calculation of NEM shape functions of the Sibson type; 3.2.1. Stage-1: insertion of point x in the existing constrained Voronoi diagram(CVD); 3.2.1.1. Look for a tetrahedron which contains point x; 3.2.1.2. Note concerning the problem of flat tetrahedrons; 3.2.2. Stage-2: calculation of the volume measurement common to ćx and cv
3.2.2.1. By the recursive Lasserre algorithm3.2.2.2. By means of a complementary volume; 3.2.2.3. By topological approach based on the CVD; 3.2.2.4. By topological approach based on the Constrained Delaunay tetrahedization(CDT); 3.2.2.5. Using the Watson algorithm; 3.2.3. Comparative test of the various algorithms; 3.3. Numerical integration; 3.3.1. Decomposition of shape function supports; 3.3.2. Stabilized nodal integration; 3.3.3. Discussion in connection with various quadratures; 3.3.3.1. 2D patch test with a technique of decomposition of shape function supports
3.3.3.2. 2D patch test with stabilized nodal integration3.3.3.3. 3D patch tests; 3.4. NEM on an octree structure; 3.4.1. Structure of the data; 3.4.1.1. Description of the geometry; 3.4.1.2. Interpolation on a quadtree; 3.4.1.3. Numerical integration; 3.4.2. Application of the boundary conditions - interface conditions; 3.4.2.1. Dirichlet-type boundary conditions: use of R-functions; 3.4.2.2. Neumann-type boundary conditions; 3.4.2.3. Partition of unity method; Chapter 4. Applications in the Mechanics of Structures and Processes; 4.1. Two- and three-dimensional elasticity
4.2. Indicators and estimators of error: adaptivity
Record Nr. UNINA-9910139056503321
Chinesta Francisco  
London, : ISTE
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Natural element method for the simulation of structures and processes [[electronic resource] /] / Francisco Chinesta ... [et al.]
Natural element method for the simulation of structures and processes [[electronic resource] /] / Francisco Chinesta ... [et al.]
Autore Chinesta Francisco
Pubbl/distr/stampa London, : ISTE
Descrizione fisica 1 online resource (255 p.)
Disciplina 624.1/7015118
624.17015118
Altri autori (Persone) ChinestaFrancisco
Collana ISTE
Soggetto topico Materials - Mechanical properties - Mathematical models
Numerical analysis
Numbers, Natural
ISBN 1-118-61690-1
1-299-31421-X
1-118-61668-5
Classificazione MAT003000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Natural Element Method for the Simulation of Structures and Processes; Title Page; Copyright Page; Table of Contents; Foreword; Acknowledgements; Chapter 1. Introduction; 1.1. SPH method; 1.2. RKPM method; 1.2.1. Conditions of reproduction; 1.2.2. Correction of the kernel; 1.2.3. Discrete form of the approximation; 1.3. MLS based approximations; 1.4. Final note; Chapter 2. Basics of the Natural Element Method; 2.1. Introduction; 2.2. Natural neighbor Galerkin methods; 2.2.1. Interpolation of natural neighbors; 2.2.2. Discretization
2.2.3. Properties of the interpolant based on natural neighbors2.3. Exact imposition of the essential boundary conditions; 2.3.1. Introduction to alpha shapes; 2.3.2. CNEM approaches; 2.4. Mixed approximations of natural neighbor type; 2.4.1. Considering the restriction of incompressibility; 2.4.2. Mixed approximations in the Galerkin method; 2.4.3. Natural neighbor partition of unity; 2.4.3.1. Partition of unity method; 2.4.3.2. Enrichment of the natural neighbor interpolants; 2.5. High order natural neighbor interpolants; 2.5.1. Hiyoshi-Sugihara interpolant
2.5.2. The De Boor algorithm for B-splines2.5.3. B-spline surfaces and natural neighboring; 2.5.3.1. Some definitions; 2.5.3.2. Surface properties; 2.5.3.3. The case of repeated nodes; Chapter 3. Numerical Aspects; 3.1. Searching for natural neighbors; 3.2. Calculation of NEM shape functions of the Sibson type; 3.2.1. Stage-1: insertion of point x in the existing constrained Voronoi diagram(CVD); 3.2.1.1. Look for a tetrahedron which contains point x; 3.2.1.2. Note concerning the problem of flat tetrahedrons; 3.2.2. Stage-2: calculation of the volume measurement common to ćx and cv
3.2.2.1. By the recursive Lasserre algorithm3.2.2.2. By means of a complementary volume; 3.2.2.3. By topological approach based on the CVD; 3.2.2.4. By topological approach based on the Constrained Delaunay tetrahedization(CDT); 3.2.2.5. Using the Watson algorithm; 3.2.3. Comparative test of the various algorithms; 3.3. Numerical integration; 3.3.1. Decomposition of shape function supports; 3.3.2. Stabilized nodal integration; 3.3.3. Discussion in connection with various quadratures; 3.3.3.1. 2D patch test with a technique of decomposition of shape function supports
3.3.3.2. 2D patch test with stabilized nodal integration3.3.3.3. 3D patch tests; 3.4. NEM on an octree structure; 3.4.1. Structure of the data; 3.4.1.1. Description of the geometry; 3.4.1.2. Interpolation on a quadtree; 3.4.1.3. Numerical integration; 3.4.2. Application of the boundary conditions - interface conditions; 3.4.2.1. Dirichlet-type boundary conditions: use of R-functions; 3.4.2.2. Neumann-type boundary conditions; 3.4.2.3. Partition of unity method; Chapter 4. Applications in the Mechanics of Structures and Processes; 4.1. Two- and three-dimensional elasticity
4.2. Indicators and estimators of error: adaptivity
Record Nr. UNINA-9910830394703321
Chinesta Francisco  
London, : ISTE
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Natural element method for the simulation of structures and processes [[electronic resource] /] / Francisco Chinesta ... [et al.]
Natural element method for the simulation of structures and processes [[electronic resource] /] / Francisco Chinesta ... [et al.]
Autore Chinesta Francisco
Pubbl/distr/stampa London, : ISTE
Descrizione fisica 1 online resource (255 p.)
Disciplina 624.1/7015118
624.17015118
Altri autori (Persone) ChinestaFrancisco
Collana ISTE
Soggetto topico Materials - Mechanical properties - Mathematical models
Numerical analysis
Numbers, Natural
ISBN 1-118-61690-1
1-299-31421-X
1-118-61668-5
Classificazione MAT003000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Natural Element Method for the Simulation of Structures and Processes; Title Page; Copyright Page; Table of Contents; Foreword; Acknowledgements; Chapter 1. Introduction; 1.1. SPH method; 1.2. RKPM method; 1.2.1. Conditions of reproduction; 1.2.2. Correction of the kernel; 1.2.3. Discrete form of the approximation; 1.3. MLS based approximations; 1.4. Final note; Chapter 2. Basics of the Natural Element Method; 2.1. Introduction; 2.2. Natural neighbor Galerkin methods; 2.2.1. Interpolation of natural neighbors; 2.2.2. Discretization
2.2.3. Properties of the interpolant based on natural neighbors2.3. Exact imposition of the essential boundary conditions; 2.3.1. Introduction to alpha shapes; 2.3.2. CNEM approaches; 2.4. Mixed approximations of natural neighbor type; 2.4.1. Considering the restriction of incompressibility; 2.4.2. Mixed approximations in the Galerkin method; 2.4.3. Natural neighbor partition of unity; 2.4.3.1. Partition of unity method; 2.4.3.2. Enrichment of the natural neighbor interpolants; 2.5. High order natural neighbor interpolants; 2.5.1. Hiyoshi-Sugihara interpolant
2.5.2. The De Boor algorithm for B-splines2.5.3. B-spline surfaces and natural neighboring; 2.5.3.1. Some definitions; 2.5.3.2. Surface properties; 2.5.3.3. The case of repeated nodes; Chapter 3. Numerical Aspects; 3.1. Searching for natural neighbors; 3.2. Calculation of NEM shape functions of the Sibson type; 3.2.1. Stage-1: insertion of point x in the existing constrained Voronoi diagram(CVD); 3.2.1.1. Look for a tetrahedron which contains point x; 3.2.1.2. Note concerning the problem of flat tetrahedrons; 3.2.2. Stage-2: calculation of the volume measurement common to ćx and cv
3.2.2.1. By the recursive Lasserre algorithm3.2.2.2. By means of a complementary volume; 3.2.2.3. By topological approach based on the CVD; 3.2.2.4. By topological approach based on the Constrained Delaunay tetrahedization(CDT); 3.2.2.5. Using the Watson algorithm; 3.2.3. Comparative test of the various algorithms; 3.3. Numerical integration; 3.3.1. Decomposition of shape function supports; 3.3.2. Stabilized nodal integration; 3.3.3. Discussion in connection with various quadratures; 3.3.3.1. 2D patch test with a technique of decomposition of shape function supports
3.3.3.2. 2D patch test with stabilized nodal integration3.3.3.3. 3D patch tests; 3.4. NEM on an octree structure; 3.4.1. Structure of the data; 3.4.1.1. Description of the geometry; 3.4.1.2. Interpolation on a quadtree; 3.4.1.3. Numerical integration; 3.4.2. Application of the boundary conditions - interface conditions; 3.4.2.1. Dirichlet-type boundary conditions: use of R-functions; 3.4.2.2. Neumann-type boundary conditions; 3.4.2.3. Partition of unity method; Chapter 4. Applications in the Mechanics of Structures and Processes; 4.1. Two- and three-dimensional elasticity
4.2. Indicators and estimators of error: adaptivity
Record Nr. UNINA-9910841748003321
Chinesta Francisco  
London, : ISTE
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Non-parametric tests for censored data [[electronic resource] /] / Vilijandas Bagdonavičius, Julius Kruopis, Mikhail S. Nikulin
Non-parametric tests for censored data [[electronic resource] /] / Vilijandas Bagdonavičius, Julius Kruopis, Mikhail S. Nikulin
Autore Bagdonavičius V (Vilijandas)
Pubbl/distr/stampa London, : ISTE
Descrizione fisica 1 online resource (253 p.)
Disciplina 519.5
Altri autori (Persone) KruopisJulius
NikulinM. S (Mikhail Stepanovich)
Collana ISTE
Soggetto topico Nonparametric statistics
Statistical hypothesis testing
Censored observations (Statistics)
ISBN 1-118-55807-3
1-118-60213-7
1-118-60198-X
1-299-18765-X
Classificazione MAT003000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Non-parametric Tests for Censored Data; Title Page; Copyright Page; Table of Contents; Preface; Terms and Notation; Chapter 1. Censored and Truncated Data; 1.1. Right-censored data; 1.2. Left truncation; 1.3. Left truncation and right censoring; 1.4. Nelson-Aalen and Kaplan-Meier estimators; 1.5. Bibliographic notes; Chapter 2. Chi-squared Tests; 2.1. Chi-squared test for composite hypothesis; 2.2. Chi-squared test for exponential distributions; 2.3. Chi-squared tests for shape-scale distribution families; 2.3.1. Chi-squared test for the Weibull distribution
2.3.2. Chi-squared tests for the loglogistic distribution2.3.3. Chi-squared test for the lognormal distribution; 2.4. Chi-squared tests for other families; 2.4.1. Chi-squared test for the Gompertz distribution; 2.4.2. Chi-squared test for distribution with hyperbolic hazard function; 2.4.3. Bibliographic notes; 2.5. Exercises; 2.6. Answers; Chapter 3. Homogeneity Tests for Independent Populations; 3.1. Data; 3.2. Weighted logrank statistics; 3.3. Logrank test statistics as weighted sums of differences between observed and expected number of failures; 3.4. Examples of weights
3.5. Weighted logrank statistics as modified score statistics3.6. The first two moments of weighted logrank statistics; 3.7. Asymptotic properties of weighted logrank statistics; 3.8. Weighted logrank tests; 3.9. Homogeneity testing when alternatives are crossings of survival functions; 3.9.1. Alternatives; 3.9.2. Modified score statistics; 3.9.3. Limit distribution of the modified score statistics; 3.9.4. Homogeneity tests against crossing survival functions alternatives; 3.9.5. Bibliographic notes; 3.10. Exercises; 3.11. Answers; Chapter 4. Homogeneity Tests for Related Populations
4.1. Paired samples4.1.1. Data; 4.1.2. Test statistics; 4.1.3. Asymptotic distribution of the test statistic; 4.1.4. The test; 4.2. Logrank-type tests for homogeneity of related k > 2 samples; 4.3. Homogeneity tests for related samples against crossing marginal survival functions alternatives; 4.3.1. Bibliographic notes; 4.4. Exercises; 4.5. Answers; Chapter 5. Goodness-of-fit for Regression Models; 5.1. Goodness-of-fit for the semi-parametric Cox model; 5.1.1. The Cox model; 5.1.2. Alternatives to the Cox model based on expanded models; 5.1.3. The data and the modified score statistics
5.1.4. Asymptotic distribution of the modified score statistic5.1.5. Tests; 5.2. Chi-squared goodness-of-fit tests for parametric AFT models; 5.2.1. Accelerated failure time model; 5.2.2. Parametric AFT model; 5.2.3. Data; 5.2.4. Idea of test construction; 5.2.5. Asymptotic distribution of Hn and Z; 5.2.6. Test statistics; 5.3. Chi-squared test for the exponential AFT model.; 5.4. Chi-squared tests for scale-shape AFT models.; 5.4.1. Chi-squared test for the Weibull AFT model; 5.4.2. Chi-squared test for the lognormal AFT model; 5.4.3. Chi-squared test for the loglogistic AFT model
5.5. Bibliographic notes
Record Nr. UNINA-9910138865303321
Bagdonavičius V (Vilijandas)  
London, : ISTE
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Non-parametric tests for censored data [[electronic resource] /] / Vilijandas Bagdonavičius, Julius Kruopis, Mikhail S. Nikulin
Non-parametric tests for censored data [[electronic resource] /] / Vilijandas Bagdonavičius, Julius Kruopis, Mikhail S. Nikulin
Autore Bagdonavičius V (Vilijandas)
Edizione [1st ed.]
Pubbl/distr/stampa London, : ISTE
Descrizione fisica 1 online resource (253 p.)
Disciplina 519.5
Altri autori (Persone) KruopisJulius
NikulinM. S (Mikhail Stepanovich)
Collana ISTE
Soggetto topico Nonparametric statistics
Statistical hypothesis testing
Censored observations (Statistics)
ISBN 1-118-55807-3
1-118-60213-7
1-118-60198-X
1-299-18765-X
Classificazione MAT003000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Non-parametric Tests for Censored Data; Title Page; Copyright Page; Table of Contents; Preface; Terms and Notation; Chapter 1. Censored and Truncated Data; 1.1. Right-censored data; 1.2. Left truncation; 1.3. Left truncation and right censoring; 1.4. Nelson-Aalen and Kaplan-Meier estimators; 1.5. Bibliographic notes; Chapter 2. Chi-squared Tests; 2.1. Chi-squared test for composite hypothesis; 2.2. Chi-squared test for exponential distributions; 2.3. Chi-squared tests for shape-scale distribution families; 2.3.1. Chi-squared test for the Weibull distribution
2.3.2. Chi-squared tests for the loglogistic distribution2.3.3. Chi-squared test for the lognormal distribution; 2.4. Chi-squared tests for other families; 2.4.1. Chi-squared test for the Gompertz distribution; 2.4.2. Chi-squared test for distribution with hyperbolic hazard function; 2.4.3. Bibliographic notes; 2.5. Exercises; 2.6. Answers; Chapter 3. Homogeneity Tests for Independent Populations; 3.1. Data; 3.2. Weighted logrank statistics; 3.3. Logrank test statistics as weighted sums of differences between observed and expected number of failures; 3.4. Examples of weights
3.5. Weighted logrank statistics as modified score statistics3.6. The first two moments of weighted logrank statistics; 3.7. Asymptotic properties of weighted logrank statistics; 3.8. Weighted logrank tests; 3.9. Homogeneity testing when alternatives are crossings of survival functions; 3.9.1. Alternatives; 3.9.2. Modified score statistics; 3.9.3. Limit distribution of the modified score statistics; 3.9.4. Homogeneity tests against crossing survival functions alternatives; 3.9.5. Bibliographic notes; 3.10. Exercises; 3.11. Answers; Chapter 4. Homogeneity Tests for Related Populations
4.1. Paired samples4.1.1. Data; 4.1.2. Test statistics; 4.1.3. Asymptotic distribution of the test statistic; 4.1.4. The test; 4.2. Logrank-type tests for homogeneity of related k > 2 samples; 4.3. Homogeneity tests for related samples against crossing marginal survival functions alternatives; 4.3.1. Bibliographic notes; 4.4. Exercises; 4.5. Answers; Chapter 5. Goodness-of-fit for Regression Models; 5.1. Goodness-of-fit for the semi-parametric Cox model; 5.1.1. The Cox model; 5.1.2. Alternatives to the Cox model based on expanded models; 5.1.3. The data and the modified score statistics
5.1.4. Asymptotic distribution of the modified score statistic5.1.5. Tests; 5.2. Chi-squared goodness-of-fit tests for parametric AFT models; 5.2.1. Accelerated failure time model; 5.2.2. Parametric AFT model; 5.2.3. Data; 5.2.4. Idea of test construction; 5.2.5. Asymptotic distribution of Hn and Z; 5.2.6. Test statistics; 5.3. Chi-squared test for the exponential AFT model.; 5.4. Chi-squared tests for scale-shape AFT models.; 5.4.1. Chi-squared test for the Weibull AFT model; 5.4.2. Chi-squared test for the lognormal AFT model; 5.4.3. Chi-squared test for the loglogistic AFT model
5.5. Bibliographic notes
Record Nr. UNINA-9910808680503321
Bagdonavičius V (Vilijandas)  
London, : ISTE
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui