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Adaptive cooling of integrated circuits using digital microfluidics / / Philip Y. Paik, Krishnendu Chakrabarty, Vamsee K. Pamula
| Adaptive cooling of integrated circuits using digital microfluidics / / Philip Y. Paik, Krishnendu Chakrabarty, Vamsee K. Pamula |
| Autore | Paik Philip Y |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Norwood, Mass., : Artech House, 2007 |
| Descrizione fisica | 1 online resource (203 p.) |
| Disciplina |
620.106
621.3815 |
| Altri autori (Persone) |
ChakrabartyKrishnendu
PamulaVamsee K <1974-> (Vamsee Krishna) |
| Collana | Artech House integrated microsystems series |
| Soggetto topico |
Integrated circuits - Cooling
Integrated circuits - Design and construction Microfluidics |
| ISBN | 1-59693-139-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Adaptive Cooling of Integrated Circuits Using Digital Microfluidics; Contents 5; Preface 11; Chapter 1 Thermal Management of Integrated Circuits 15; Chapter 2 Cooling Devices for Integrated Circuits 33; Chapter 3 Adaptive Hot-Spot Cooling Principles and Design 49; Chapter 4 Technology Development 77; Chapter 5 Thermal Effects of Digital Microfluidic Devices 105; Chapter 6 Flow-Through-Based Adaptive Cooling 117; Chapter 7 Programmable Thermal Switch-Based Adaptive Cooling 145; Chapter 8 Concluding Remarks 161; Appendix A Image Analysis Software Using MATLAB 167. |
| Record Nr. | UNINA-9910825461903321 |
Paik Philip Y
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| Norwood, Mass., : Artech House, 2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Adaptive phased array thermotherapy for cancer / / Alan J. Fenn
| Adaptive phased array thermotherapy for cancer / / Alan J. Fenn |
| Autore | Fenn A. J (Alan Jeffrey), <1953-> |
| Pubbl/distr/stampa | Boston : , : Artech House, , ©2009 |
| Descrizione fisica | 1 online resource (240 p.) |
| Disciplina | 616.9940632 |
| Soggetto topico |
Cancer - Thermotherapy
Microwaves - Therapeutic use Microwave antennas |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-59693-380-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Adaptive Phased Array Thermotherapy for Cancer; Contents; Preface; Chapter 1: Adaptive Phased Array Thermotherapy Technique; Chapter 2: Adaptive Phased Array Algorithms for Thermotherapy; Chapter 3: Electromagnetic Field Theory for Tissue Heating; Chapter 4: Thermal Modeling Theory for Tissue Heating; Chapter 5: Adaptive Array Simulations for the Torso; Chapter 6: Phantom Studies for Deep Tumors in the Torso; Chapter 7: Monopole Phased Array for Deep Cancer; Chapter 8: Adaptive Array for Breast Cancer: Preclinical Results; Chapter 9: Adaptive Array for Breast Cancer: Clinical Results
Chapter 10: Future Studies of Adaptive Phased Arrays for Cancer About the Author; Index |
| Record Nr. | UNINA-9910455557703321 |
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Fenn A. J (Alan Jeffrey), <1953->
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| Boston : , : Artech House, , ©2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Adaptive phased array thermotherapy for cancer / / Alan J. Fenn
| Adaptive phased array thermotherapy for cancer / / Alan J. Fenn |
| Autore | Fenn A. J (Alan Jeffrey), <1953-> |
| Pubbl/distr/stampa | Boston : , : Artech House, , ©2009 |
| Descrizione fisica | 1 online resource (240 p.) |
| Disciplina | 616.9940632 |
| Soggetto topico |
Cancer - Thermotherapy
Microwaves - Therapeutic use Microwave antennas |
| ISBN | 1-59693-380-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Adaptive Phased Array Thermotherapy for Cancer; Contents; Preface; Chapter 1: Adaptive Phased Array Thermotherapy Technique; Chapter 2: Adaptive Phased Array Algorithms for Thermotherapy; Chapter 3: Electromagnetic Field Theory for Tissue Heating; Chapter 4: Thermal Modeling Theory for Tissue Heating; Chapter 5: Adaptive Array Simulations for the Torso; Chapter 6: Phantom Studies for Deep Tumors in the Torso; Chapter 7: Monopole Phased Array for Deep Cancer; Chapter 8: Adaptive Array for Breast Cancer: Preclinical Results; Chapter 9: Adaptive Array for Breast Cancer: Clinical Results
Chapter 10: Future Studies of Adaptive Phased Arrays for Cancer About the Author; Index |
| Record Nr. | UNINA-9910778599203321 |
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Fenn A. J (Alan Jeffrey), <1953->
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||
| Boston : , : Artech House, , ©2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Adaptive phased array thermotherapy for cancer / / Alan J. Fenn
| Adaptive phased array thermotherapy for cancer / / Alan J. Fenn |
| Autore | Fenn A. J (Alan Jeffrey), <1953-> |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Boston, : Artech House, c2009 |
| Descrizione fisica | 1 online resource (240 p.) |
| Disciplina | 616.9940632 |
| Soggetto topico |
Cancer - Thermotherapy
Microwaves - Therapeutic use Microwave antennas |
| ISBN | 1-59693-380-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Adaptive Phased Array Thermotherapy for Cancer; Contents; Preface; Chapter 1: Adaptive Phased Array Thermotherapy Technique; Chapter 2: Adaptive Phased Array Algorithms for Thermotherapy; Chapter 3: Electromagnetic Field Theory for Tissue Heating; Chapter 4: Thermal Modeling Theory for Tissue Heating; Chapter 5: Adaptive Array Simulations for the Torso; Chapter 6: Phantom Studies for Deep Tumors in the Torso; Chapter 7: Monopole Phased Array for Deep Cancer; Chapter 8: Adaptive Array for Breast Cancer: Preclinical Results; Chapter 9: Adaptive Array for Breast Cancer: Clinical Results
Chapter 10: Future Studies of Adaptive Phased Arrays for Cancer About the Author; Index |
| Record Nr. | UNINA-9910811016403321 |
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Fenn A. J (Alan Jeffrey), <1953->
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| Boston, : Artech House, c2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Adaptive Radar Detection : Model-Based, Data-Driven and Hybrid Approaches / / Angelo Coluccia
| Adaptive Radar Detection : Model-Based, Data-Driven and Hybrid Approaches / / Angelo Coluccia |
| Autore | Coluccia Angelo |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Norwood, MA : , : Artech House, , [2023] |
| Descrizione fisica | 1 online resource (235 pages) |
| Disciplina | 621.3848 |
| Soggetto topico | Adaptive signal processing |
| ISBN |
9781630819019
1-63081-901-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Adaptive Radar Detection Model-Based, Data-Driven, and Hybrid Approaches -- Contents -- Preface -- Acknowledgments -- 1 Model-Based Adaptive Radar Detection -- 1.1 Introduction to Radar Processing -- 1.1.1 Generalities and Basic Terminology of Coherent Radars -- 1.1.2 Array Processing and Space-Time Adaptive Processing -- 1.1.3 Target Detection and Performance Metrics -- 1.2 Unstructured Signal in White Noise -- 1.2.1 Old but Gold: Basic Signal Detection and the Energy Detector -- 1.2.2 The Neyman-Pearson Approach -- 1.2.3 Adaptive CFAR Detection -- 1.2.4 Correlated Signal Model in White Noise -- 1.3 Structured Signal in White Noise -- 1.3.1 Detection of a Structured Signal in White Noise and Matched Filter -- 1.3.2 Generalized Likelihood Ratio Test -- 1.3.3 Detection of an Unknown Rank-One Signal in White Noise -- 1.3.4 Steering Vector Known up to a Parameter and Doppler Processing -- 1.4 Adaptive Detection in Colored Noise -- 1.4.1 One-Step, Two-Step, and Decoupled Processing -- 1.4.2 General Hypothesis Testing Problem via GLRT: A Comparison -- 1.4.3 Behavior under Mismatched Conditions: Robustness vs Selectivity -- 1.4.4 Model-Based Design of Adaptive Detectors -- 1.5 Summary -- References -- 2 Classification Problems and Data-Driven Tools -- 2.1 General Decision Problems and Classification -- 2.1.1 M-ary Decision Problems -- 2.1.2 Classifiers and Decision Regions -- 2.1.3 Binary Classification vs Radar Detection -- 2.1.4 Signal Representation and Universal Approximation -- 2.2 Learning Approaches and Classification Algorithms -- 2.2.1 Statistical Learning -- 2.2.2 Bias-Variance Trade-Off -- 2.3 Data-Driven Classifiers -- 2.3.1 k-Nearest Neighbors -- 2.3.2 Linear Methods for Dimensionality Reduction and Classification -- 2.3.3 Support Vector Machine and Kernel Methods -- 2.3.4 Decision Trees and Random Forests.
2.3.5 Other Machine Learning Tools -- 2.4 Neural Networks and Deep Learning -- 2.4.1 Multilayer Perceptron -- 2.4.2 Feature Engineering vs Feature Learning -- 2.4.3 Deep Learning -- 2.5 Summary -- References -- 3 Radar Applications of Machine Learning -- 3.1 Data-Driven Radar Applications -- 3.2 Classification of Communication and Radar Signals -- 3.2.1 Automatic Modulation Recognition and Physical-Layer Applications -- 3.2.2 Datasets and Experimentation -- 3.2.3 Classification of Radar Signals and Radiation Sources -- 3.3 Detection Based on Supervised Machine Learning -- 3.3.1 SVM-Based Detection with Controlled PFA -- 3.3.2 Decision Tree-Based Detection with Controlled PFA -- 3.3.3 Revisiting the Neyman-Pearson Approach -- 3.3.4 SVM and NN for CFAR Processing -- 3.3.5 Feature Spaces with (Generalized) CFAR Property -- 3.3.6 Deep Learning Based Detection -- 3.4 Other Approaches -- 3.4.1 Unsupervised Learning and Anomaly Detection -- 3.4.2 Reinforcement Learning -- 3.5 Summary -- References -- 4 Hybrid Model-Based and Data-Driven Detection -- 4.1 Concept Drift, Retraining, and Adaptiveness -- 4.2 Hybridization Approaches -- 4.2.1 Different Dimensions of Hybridization -- 4.2.2 Hybrid Model-Based and Data-Driven Ideas in Signal Processing and Communications -- 4.3 Feature Spaces Based onWell-Known Statistics or Raw Data -- 4.3.1 Nonparametric Learning: k-Nearest Neighbor -- 4.3.2 Quasi-Whitened Raw Data as Feature Vector -- 4.3.3 Well-Known CFAR Statistics as a Feature Vector -- 4.4 Rethinking Model-Based Detection in a CFAR Feature Space -- 4.4.1 Maximal Invariant Feature Space -- 4.4.2 Characterizing Model-Based Detectors in CFAR-FP -- 4.4.3 Design Strategies in the CFAR-FP -- 4.5 Summary -- References -- 5 Theories, Interpretability, and Other Open Issues -- 5.1 Challenges in Machine Learning -- 5.2 Theories for (Deep) Neural Networks. 5.2.1 Network Structures and Unrolling -- 5.2.2 Information Theory, Coding, and Sparse Representation -- 5.2.3 Universal Mapping, Expressiveness, and Generalization -- 5.2.4 Overparametrized Interpolation, Reproducing Kernel Hilbert Spaces, and Double Descent -- 5.2.5 Mathematics of Deep Learning, Statistical Mechanics, and Signal Processing -- 5.3 Open Issues -- 5.3.1 Adversarial Attacks -- 5.3.2 Stability, Efficiency, and Interpretability -- 5.3.3 Visualization -- 5.3.4 Sustainability, Marginal Return, and Patentability -- 5.4 Summary -- References -- List of Acronyms -- List of Symbols -- About the Author -- Index. |
| Record Nr. | UNINA-9910795724403321 |
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Coluccia Angelo
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||
| Norwood, MA : , : Artech House, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Adaptive Radar Detection : Model-Based, Data-Driven and Hybrid Approaches / / Angelo Coluccia
| Adaptive Radar Detection : Model-Based, Data-Driven and Hybrid Approaches / / Angelo Coluccia |
| Autore | Coluccia Angelo |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Norwood, MA : , : Artech House, , [2023] |
| Descrizione fisica | 1 online resource (235 pages) |
| Disciplina | 621.3848 |
| Soggetto topico | Adaptive signal processing |
| ISBN |
9781630819019
1-63081-901-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Adaptive Radar Detection Model-Based, Data-Driven, and Hybrid Approaches -- Contents -- Preface -- Acknowledgments -- 1 Model-Based Adaptive Radar Detection -- 1.1 Introduction to Radar Processing -- 1.1.1 Generalities and Basic Terminology of Coherent Radars -- 1.1.2 Array Processing and Space-Time Adaptive Processing -- 1.1.3 Target Detection and Performance Metrics -- 1.2 Unstructured Signal in White Noise -- 1.2.1 Old but Gold: Basic Signal Detection and the Energy Detector -- 1.2.2 The Neyman-Pearson Approach -- 1.2.3 Adaptive CFAR Detection -- 1.2.4 Correlated Signal Model in White Noise -- 1.3 Structured Signal in White Noise -- 1.3.1 Detection of a Structured Signal in White Noise and Matched Filter -- 1.3.2 Generalized Likelihood Ratio Test -- 1.3.3 Detection of an Unknown Rank-One Signal in White Noise -- 1.3.4 Steering Vector Known up to a Parameter and Doppler Processing -- 1.4 Adaptive Detection in Colored Noise -- 1.4.1 One-Step, Two-Step, and Decoupled Processing -- 1.4.2 General Hypothesis Testing Problem via GLRT: A Comparison -- 1.4.3 Behavior under Mismatched Conditions: Robustness vs Selectivity -- 1.4.4 Model-Based Design of Adaptive Detectors -- 1.5 Summary -- References -- 2 Classification Problems and Data-Driven Tools -- 2.1 General Decision Problems and Classification -- 2.1.1 M-ary Decision Problems -- 2.1.2 Classifiers and Decision Regions -- 2.1.3 Binary Classification vs Radar Detection -- 2.1.4 Signal Representation and Universal Approximation -- 2.2 Learning Approaches and Classification Algorithms -- 2.2.1 Statistical Learning -- 2.2.2 Bias-Variance Trade-Off -- 2.3 Data-Driven Classifiers -- 2.3.1 k-Nearest Neighbors -- 2.3.2 Linear Methods for Dimensionality Reduction and Classification -- 2.3.3 Support Vector Machine and Kernel Methods -- 2.3.4 Decision Trees and Random Forests.
2.3.5 Other Machine Learning Tools -- 2.4 Neural Networks and Deep Learning -- 2.4.1 Multilayer Perceptron -- 2.4.2 Feature Engineering vs Feature Learning -- 2.4.3 Deep Learning -- 2.5 Summary -- References -- 3 Radar Applications of Machine Learning -- 3.1 Data-Driven Radar Applications -- 3.2 Classification of Communication and Radar Signals -- 3.2.1 Automatic Modulation Recognition and Physical-Layer Applications -- 3.2.2 Datasets and Experimentation -- 3.2.3 Classification of Radar Signals and Radiation Sources -- 3.3 Detection Based on Supervised Machine Learning -- 3.3.1 SVM-Based Detection with Controlled PFA -- 3.3.2 Decision Tree-Based Detection with Controlled PFA -- 3.3.3 Revisiting the Neyman-Pearson Approach -- 3.3.4 SVM and NN for CFAR Processing -- 3.3.5 Feature Spaces with (Generalized) CFAR Property -- 3.3.6 Deep Learning Based Detection -- 3.4 Other Approaches -- 3.4.1 Unsupervised Learning and Anomaly Detection -- 3.4.2 Reinforcement Learning -- 3.5 Summary -- References -- 4 Hybrid Model-Based and Data-Driven Detection -- 4.1 Concept Drift, Retraining, and Adaptiveness -- 4.2 Hybridization Approaches -- 4.2.1 Different Dimensions of Hybridization -- 4.2.2 Hybrid Model-Based and Data-Driven Ideas in Signal Processing and Communications -- 4.3 Feature Spaces Based onWell-Known Statistics or Raw Data -- 4.3.1 Nonparametric Learning: k-Nearest Neighbor -- 4.3.2 Quasi-Whitened Raw Data as Feature Vector -- 4.3.3 Well-Known CFAR Statistics as a Feature Vector -- 4.4 Rethinking Model-Based Detection in a CFAR Feature Space -- 4.4.1 Maximal Invariant Feature Space -- 4.4.2 Characterizing Model-Based Detectors in CFAR-FP -- 4.4.3 Design Strategies in the CFAR-FP -- 4.5 Summary -- References -- 5 Theories, Interpretability, and Other Open Issues -- 5.1 Challenges in Machine Learning -- 5.2 Theories for (Deep) Neural Networks. 5.2.1 Network Structures and Unrolling -- 5.2.2 Information Theory, Coding, and Sparse Representation -- 5.2.3 Universal Mapping, Expressiveness, and Generalization -- 5.2.4 Overparametrized Interpolation, Reproducing Kernel Hilbert Spaces, and Double Descent -- 5.2.5 Mathematics of Deep Learning, Statistical Mechanics, and Signal Processing -- 5.3 Open Issues -- 5.3.1 Adversarial Attacks -- 5.3.2 Stability, Efficiency, and Interpretability -- 5.3.3 Visualization -- 5.3.4 Sustainability, Marginal Return, and Patentability -- 5.4 Summary -- References -- List of Acronyms -- List of Symbols -- About the Author -- Index. |
| Record Nr. | UNINA-9910824862403321 |
|
Coluccia Angelo
|
||
| Norwood, MA : , : Artech House, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advanced computational electromagnetic methods and applications / / Wenhua Yu [and three others], editors
| Advanced computational electromagnetic methods and applications / / Wenhua Yu [and three others], editors |
| Pubbl/distr/stampa | Boston ; ; London : , : Artech House, , [2015] |
| Descrizione fisica | 1 online resource (597 p.) |
| Disciplina | 537.0285 |
| Collana | Artech House antennas and electromagnetics analysis library Advanced computational electromagnetic methods and applications |
| Soggetto topico |
Electromagnetism - Data processing
Electromagnetism - Computer simulation |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-5231-1693-5
1-60807-897-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro; Advanced Computational Electromagnetic Methods and Applications; Contents; Preface; Chapter 1 Novelties of Spectral Domain Analysis in Antenna Characterizations: Concept, Formulation, and Applications; Chapter 2 High-Order FDTD Methods; Chapter 3 GPU Acceleration of FDTD Method for Simulation of Microwave Circuits; Chapter 4 Recent FDTD Advances for Electromagnetic Wave Propagation in the Ionosphere; Chapter 5 Phi Coprocessor Acceleration Techniques in Computational Electromagnetic Methods
Chapter 6 Domain Decomposition Methods for Finite Element Analysis of Large-Scale Electromagnetic Problems Chapter 7 High-Accuracy Computations for Electromagnetic Integral Equations; Chapter 8 Fast Electromagnetic Solver Based on Randomized Pseudo-Skeleton Approximation; Chapter 9 Computational Electromagnetics for the Evaluation of EMC Issues in Multicomponen tEnergy Systems; Chapter 10 Manipulation of Electromagnetic Waves Based on New Unique Metamaterials: Theory and Applications; Chapter 11 Time-Domain Integral Equation Method for Transient Problems Chapter 12 Statistical Methods and Computational Electromagnetics Applied to Human Exposure Assessment About the Authors; Index; 1.1 INTRODUCTION; 1.2 ANTENNA RADIATION ANALYSIS IN THE SPECTRAL DOMAIN; 1.3 OBTAINING THE PLANE WAVE SPECTRUM FROM FAR-FIELD PATTERNS AND RADIATED POWER; 1.4 PLANE WAVE SPECTRUM COMPUTATION VIA FAST FOURIER TRANSFORM; 1.5 COORDINATE TRANSFORMATIONS FOR GENERALIZED SIMULATION AND MEASUREMENT SYSTEMS; 1.6 THEORETICAL VALIDATION OF NEAR-FIELD PREDICTION; 1.7 SOME PRACTICAL EXAMPLES; REFERENCES; 2.1 FOURTH ORDER DIFFERENCES IN FDTD DISCRETE SPACE 2.2 SEAMLESS HYBRID S24/FDTD SIMULATIONS2.3 ABSORBING BOUNDARY CONDITIONS; 2.4 POINT CURRENT AND FIELD SOURCES; 2.5 PLANE WAVE SOURCES; 2.6 PEC MODELING; 2.7 ADVANCED FORMS OF HIGH-ORDER FDTD ALGORITHMS; REFERENCES; 3.1 INTRODUCTION; 3.2 FDTD CODE FOR MICROWAVE CIRCUIT SIMULATION; 3.3 FDTD CODE USING CUDA; 3.4 NUMERICAL RESULTS; REFERENCES; 4.1 INTRODUCTION; 4.2 CURRENT STATE OF THE ART; 4.3 FDTD EARTH-IONOSPHERE MODEL OVERVIEW; 4.4 NEW MAGNETIZED IONOSPHERIC PLASMA ALGORITHM; 4.5 STOCHASTIC FDTD (S-FDTD); 4.6 INPUT TO FDTD/S-FDTD EARTH-PLAMSA IONOSPHERE MODELS; 4.7 CONCLUSIONS; REFERENCES 5.1 INTRODUCTION5.2 ENVIRONMENT REQUIREMENTS AND SETTINGS; 5.3 CODE DEVELOPMENT; 5.4 NUMERICAL RESULTS; REFERENCES; 6.1 FETI METHODS WITH ONE AND TWO LAGRANGE MULTIPLIERS; 6.2 FETI-DP METHODS WITH ONE AND TWO LAGRANGE MULTIPLIERS; 6.3 LM-BASED NONCONFORMAL FETI-DP METHOD; 6.4 CE-BASED NONCONFORMAL FETI-DP METHOD; 6.5 FETI-DP METHOD ENHANCED BY THE SECOND-ORDER TRANSMISSION CONDITION; 6.6 HYBRID NONCONFORMAL FETI/CONFORMAL FETI-DP METHOD; 6.7 NUMERICAL EXAMPLES; 6.8 SUMMARY; REFERENCES; 7.1 NORMALIZED RESIDUAL ERROR; 7.2 HIGH-ORDER TREATMENT OF SMOOTH TARGETS; 7.3 THE DIPOLE ANTENNA 7.4 HIGH-ORDER TREATMENT OF WEDGE SINGULARITIES |
| Record Nr. | UNINA-9910467580503321 |
| Boston ; ; London : , : Artech House, , [2015] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advanced computational electromagnetic methods and applications / / Wenhua Yu [and three others], editors
| Advanced computational electromagnetic methods and applications / / Wenhua Yu [and three others], editors |
| Pubbl/distr/stampa | Boston ; ; London : , : Artech House, , [2015] |
| Descrizione fisica | 1 online resource (597 p.) |
| Disciplina | 537.0285 |
| Collana | Artech House antennas and electromagnetics analysis library Advanced computational electromagnetic methods and applications |
| Soggetto topico |
Electromagnetism - Data processing
Electromagnetism - Computer simulation |
| ISBN |
1-5231-1693-5
1-60807-897-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro; Advanced Computational Electromagnetic Methods and Applications; Contents; Preface; Chapter 1 Novelties of Spectral Domain Analysis in Antenna Characterizations: Concept, Formulation, and Applications; Chapter 2 High-Order FDTD Methods; Chapter 3 GPU Acceleration of FDTD Method for Simulation of Microwave Circuits; Chapter 4 Recent FDTD Advances for Electromagnetic Wave Propagation in the Ionosphere; Chapter 5 Phi Coprocessor Acceleration Techniques in Computational Electromagnetic Methods
Chapter 6 Domain Decomposition Methods for Finite Element Analysis of Large-Scale Electromagnetic Problems Chapter 7 High-Accuracy Computations for Electromagnetic Integral Equations; Chapter 8 Fast Electromagnetic Solver Based on Randomized Pseudo-Skeleton Approximation; Chapter 9 Computational Electromagnetics for the Evaluation of EMC Issues in Multicomponen tEnergy Systems; Chapter 10 Manipulation of Electromagnetic Waves Based on New Unique Metamaterials: Theory and Applications; Chapter 11 Time-Domain Integral Equation Method for Transient Problems Chapter 12 Statistical Methods and Computational Electromagnetics Applied to Human Exposure Assessment About the Authors; Index; 1.1 INTRODUCTION; 1.2 ANTENNA RADIATION ANALYSIS IN THE SPECTRAL DOMAIN; 1.3 OBTAINING THE PLANE WAVE SPECTRUM FROM FAR-FIELD PATTERNS AND RADIATED POWER; 1.4 PLANE WAVE SPECTRUM COMPUTATION VIA FAST FOURIER TRANSFORM; 1.5 COORDINATE TRANSFORMATIONS FOR GENERALIZED SIMULATION AND MEASUREMENT SYSTEMS; 1.6 THEORETICAL VALIDATION OF NEAR-FIELD PREDICTION; 1.7 SOME PRACTICAL EXAMPLES; REFERENCES; 2.1 FOURTH ORDER DIFFERENCES IN FDTD DISCRETE SPACE 2.2 SEAMLESS HYBRID S24/FDTD SIMULATIONS2.3 ABSORBING BOUNDARY CONDITIONS; 2.4 POINT CURRENT AND FIELD SOURCES; 2.5 PLANE WAVE SOURCES; 2.6 PEC MODELING; 2.7 ADVANCED FORMS OF HIGH-ORDER FDTD ALGORITHMS; REFERENCES; 3.1 INTRODUCTION; 3.2 FDTD CODE FOR MICROWAVE CIRCUIT SIMULATION; 3.3 FDTD CODE USING CUDA; 3.4 NUMERICAL RESULTS; REFERENCES; 4.1 INTRODUCTION; 4.2 CURRENT STATE OF THE ART; 4.3 FDTD EARTH-IONOSPHERE MODEL OVERVIEW; 4.4 NEW MAGNETIZED IONOSPHERIC PLASMA ALGORITHM; 4.5 STOCHASTIC FDTD (S-FDTD); 4.6 INPUT TO FDTD/S-FDTD EARTH-PLAMSA IONOSPHERE MODELS; 4.7 CONCLUSIONS; REFERENCES 5.1 INTRODUCTION5.2 ENVIRONMENT REQUIREMENTS AND SETTINGS; 5.3 CODE DEVELOPMENT; 5.4 NUMERICAL RESULTS; REFERENCES; 6.1 FETI METHODS WITH ONE AND TWO LAGRANGE MULTIPLIERS; 6.2 FETI-DP METHODS WITH ONE AND TWO LAGRANGE MULTIPLIERS; 6.3 LM-BASED NONCONFORMAL FETI-DP METHOD; 6.4 CE-BASED NONCONFORMAL FETI-DP METHOD; 6.5 FETI-DP METHOD ENHANCED BY THE SECOND-ORDER TRANSMISSION CONDITION; 6.6 HYBRID NONCONFORMAL FETI/CONFORMAL FETI-DP METHOD; 6.7 NUMERICAL EXAMPLES; 6.8 SUMMARY; REFERENCES; 7.1 NORMALIZED RESIDUAL ERROR; 7.2 HIGH-ORDER TREATMENT OF SMOOTH TARGETS; 7.3 THE DIPOLE ANTENNA 7.4 HIGH-ORDER TREATMENT OF WEDGE SINGULARITIES |
| Record Nr. | UNINA-9910794618703321 |
| Boston ; ; London : , : Artech House, , [2015] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advanced computational electromagnetic methods and applications / / Wenhua Yu [and three others], editors
| Advanced computational electromagnetic methods and applications / / Wenhua Yu [and three others], editors |
| Pubbl/distr/stampa | Boston ; ; London : , : Artech House, , [2015] |
| Descrizione fisica | 1 online resource (597 p.) |
| Disciplina | 537.0285 |
| Collana | Artech House antennas and electromagnetics analysis library Advanced computational electromagnetic methods and applications |
| Soggetto topico |
Electromagnetism - Data processing
Electromagnetism - Computer simulation |
| ISBN |
1-5231-1693-5
1-60807-897-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro; Advanced Computational Electromagnetic Methods and Applications; Contents; Preface; Chapter 1 Novelties of Spectral Domain Analysis in Antenna Characterizations: Concept, Formulation, and Applications; Chapter 2 High-Order FDTD Methods; Chapter 3 GPU Acceleration of FDTD Method for Simulation of Microwave Circuits; Chapter 4 Recent FDTD Advances for Electromagnetic Wave Propagation in the Ionosphere; Chapter 5 Phi Coprocessor Acceleration Techniques in Computational Electromagnetic Methods
Chapter 6 Domain Decomposition Methods for Finite Element Analysis of Large-Scale Electromagnetic Problems Chapter 7 High-Accuracy Computations for Electromagnetic Integral Equations; Chapter 8 Fast Electromagnetic Solver Based on Randomized Pseudo-Skeleton Approximation; Chapter 9 Computational Electromagnetics for the Evaluation of EMC Issues in Multicomponen tEnergy Systems; Chapter 10 Manipulation of Electromagnetic Waves Based on New Unique Metamaterials: Theory and Applications; Chapter 11 Time-Domain Integral Equation Method for Transient Problems Chapter 12 Statistical Methods and Computational Electromagnetics Applied to Human Exposure Assessment About the Authors; Index; 1.1 INTRODUCTION; 1.2 ANTENNA RADIATION ANALYSIS IN THE SPECTRAL DOMAIN; 1.3 OBTAINING THE PLANE WAVE SPECTRUM FROM FAR-FIELD PATTERNS AND RADIATED POWER; 1.4 PLANE WAVE SPECTRUM COMPUTATION VIA FAST FOURIER TRANSFORM; 1.5 COORDINATE TRANSFORMATIONS FOR GENERALIZED SIMULATION AND MEASUREMENT SYSTEMS; 1.6 THEORETICAL VALIDATION OF NEAR-FIELD PREDICTION; 1.7 SOME PRACTICAL EXAMPLES; REFERENCES; 2.1 FOURTH ORDER DIFFERENCES IN FDTD DISCRETE SPACE 2.2 SEAMLESS HYBRID S24/FDTD SIMULATIONS2.3 ABSORBING BOUNDARY CONDITIONS; 2.4 POINT CURRENT AND FIELD SOURCES; 2.5 PLANE WAVE SOURCES; 2.6 PEC MODELING; 2.7 ADVANCED FORMS OF HIGH-ORDER FDTD ALGORITHMS; REFERENCES; 3.1 INTRODUCTION; 3.2 FDTD CODE FOR MICROWAVE CIRCUIT SIMULATION; 3.3 FDTD CODE USING CUDA; 3.4 NUMERICAL RESULTS; REFERENCES; 4.1 INTRODUCTION; 4.2 CURRENT STATE OF THE ART; 4.3 FDTD EARTH-IONOSPHERE MODEL OVERVIEW; 4.4 NEW MAGNETIZED IONOSPHERIC PLASMA ALGORITHM; 4.5 STOCHASTIC FDTD (S-FDTD); 4.6 INPUT TO FDTD/S-FDTD EARTH-PLAMSA IONOSPHERE MODELS; 4.7 CONCLUSIONS; REFERENCES 5.1 INTRODUCTION5.2 ENVIRONMENT REQUIREMENTS AND SETTINGS; 5.3 CODE DEVELOPMENT; 5.4 NUMERICAL RESULTS; REFERENCES; 6.1 FETI METHODS WITH ONE AND TWO LAGRANGE MULTIPLIERS; 6.2 FETI-DP METHODS WITH ONE AND TWO LAGRANGE MULTIPLIERS; 6.3 LM-BASED NONCONFORMAL FETI-DP METHOD; 6.4 CE-BASED NONCONFORMAL FETI-DP METHOD; 6.5 FETI-DP METHOD ENHANCED BY THE SECOND-ORDER TRANSMISSION CONDITION; 6.6 HYBRID NONCONFORMAL FETI/CONFORMAL FETI-DP METHOD; 6.7 NUMERICAL EXAMPLES; 6.8 SUMMARY; REFERENCES; 7.1 NORMALIZED RESIDUAL ERROR; 7.2 HIGH-ORDER TREATMENT OF SMOOTH TARGETS; 7.3 THE DIPOLE ANTENNA 7.4 HIGH-ORDER TREATMENT OF WEDGE SINGULARITIES |
| Record Nr. | UNINA-9910824248803321 |
| Boston ; ; London : , : Artech House, , [2015] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advanced FDTD methods : parallelization, acceleration, and engineering applications / / Wenha Yu [and others]
| Advanced FDTD methods : parallelization, acceleration, and engineering applications / / Wenha Yu [and others] |
| Autore | Yu Wenhua |
| Pubbl/distr/stampa | Boston : , : Artech House, , ©2011 |
| Descrizione fisica | 1 online resource (266 p.) |
| Disciplina | 621.3 |
| Altri autori (Persone) | YuWenhua |
| Collana | Artech House electromagnetics series |
| Soggetto topico |
Finite differences
Time-domain analysis |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-60807-177-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Advanced FDTD Methods: Parallelization, Acceleration, and Engineering Applications; Contents; Preface; Chapter 1 Computational Electromagnetic Methods; Chapter 2 FDTD Optimization and Acceleration; Chapter 3 Parallel FDTD Method and Systems; Chapter 4 Electromagnetic Simulation Techniques; Chapter 5 EM Simulation Software Benchmarks; Chapter 6 Large Multiscale Problem Solving; Chapter 7 Summary; Appendix A Antenna Power and Efficiency; Appendix B Active Reflection Coefficient; Appendix C Total Active Reflection Coefficient; Appendix D MEG and ECC
Appendix E Lossy Dielectric Simulation TechniqueAppendix F Circular Polarization Decomposition; Appendix G Vector Fitting Technique; Appendix H Partially Symmetric Problem Simulation; Appendix I Time-Domain Reflectometry (TDR); Appendix J S-Parameter Extraction; Appendix K Debye Model Construction; Appendix L Geometry Mapping Technique; Appendix M PC Cluster Optimization; About the Authors; Index |
| Record Nr. | UNINA-9910460076803321 |
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Yu Wenhua
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| Boston : , : Artech House, , ©2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
