Search Results - ("algorithm" OR "algorithms")

Time-frequency domain for segmentation and classification of non-stationary signals : the Stockwell Transform applied on bio-signals and electric signals by Moukadem, Ali, Abdeslam, Djaffar Ould, Dieterlen, Alain

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Sensors, mechatronics and automation : selected, peer reviewed papers from the 2013 International Conference on Sensors, Mechatronics and Automation (ICSMA 2013), December 24-25, 2...

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Mount Sinai expert guides. Gastroenterology

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Content-based image classification : efficient machine learning using robust feature extraction techniques by Das, Rik, 1978-

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CUDA Application Design and Development. by Farber, Rob

Table of Contents: “…Front Cover -- CUDA Application Design and Development -- Copyright -- Dedication -- Table of Contents -- Foreword -- Preface -- 1 First Programs and How to Think in CUDA -- Source Code and Wiki -- Distinguishing CUDA from Conventional Programming with a Simple Example -- Choosing a CUDA API -- Some Basic CUDA Concepts -- Understanding Our First Runtime Kernel -- Three Rules of GPGPU Programming -- Rule 1: Get the Data on the GPU and Keep It There -- Rule 2: Give the GPGPU Enough Work to Do -- Rule 3: Focus on Data Reuse within the GPGPU to Avoid Memory Bandwidth Limitations -- Big-O Considerations and Data Transfers -- CUDA and Amdahl's Law -- Data and Task Parallelism -- Hybrid Execution: Using Both CPU and GPU Resources -- Regression Testing and Accuracy -- Silent Errors -- Introduction to Debugging -- UNIX Debugging -- NVIDIA's cuda-gdb Debugger -- The CUDA Memory Checker -- Use cuda-gdb with the UNIX ddd Interface -- Windows Debugging with Parallel Nsight -- Summary -- 2 CUDA for Machine Learning and Optimization -- Modeling and Simulation -- Fitting Parameterized Models -- Nelder-Mead Method -- Levenberg-Marquardt Method -- Algorithmic Speedups -- Machine Learning and Neural Networks -- XOR: An Important Nonlinear Machine-Learning Problem -- An Example Objective Function -- A Complete Functor for Multiple GPU Devices and the Host Processors -- Brief Discussion of a Complete Nelder-Mead Optimization Code -- Performance Results on XOR -- Performance Discussion -- Summary -- The C++ Nelder-Mead Template -- 3 The CUDA Tool Suite: Profiling a PCA/NLPCA Functor -- PCA and NLPCA -- Autoencoders -- An Example Functor for PCA Analysis -- An Example Functor for NLPCA Analysis -- Obtaining Basic Profile Information -- Gprof: A Common UNIX Profiler -- The NVIDIA Visual Profiler: Computeprof -- Parallel Nsight for Microsoft Visual Studio.…”
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Engineering autonomous vehicles and robots : the DragonFly modular-based approach by Liu, Shaoshan

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Space antenna handbook

Table of Contents: “…1.3.4 Helical Antennas1.3.5 Printed Antennas; 1.4 Arrays; 1.4.1 Array Configurations; 1.5 Basic Effects of Antennas in the Space Environment; 1.5.1 Multipaction; 1.5.2 Passive Inter-modulation; 1.5.3 Outgassing; References; 2 Space Antenna Modeling; 2.1 Introduction; 2.1.1 Maxwell's Equations; 2.1.2 CEM; 2.2 Methods of Antenna Modeling; 2.2.1 Basic Theory; 2.2.2 Method of Moments; 2.2.3 FEM; 2.2.4 FDTD Method; 2.3 Fast Algorithms for Large Space Antenna Modeling; 2.3.1 Introduction; 2.3.2 MLFMA; 2.3.3 Hierarchical Basis for the FEM.…”
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Metamodeling-Driven IP Reuse for SoC Integration and Microprocessor Design. by Mathaikutty, Deepak A.

Table of Contents: “…Support for IP IntegratorEssential Issues with Verification IP Reuse; (1) Modeling Language; (2) Generation Algorithms; 1.4 METAMODELING APPROACH TO REUSE; 1.5 PROBLEM STATEMENT; 1.6 RESEARCH CONTRIBUTIONS; 1.7 TOOLS AND TECHNIQUES DEVELOPED; References; Chapter 2 Background; 2.1 METAMODELING; 2.1.1 Implicit Metamodeling Versus Explicit Metamodeling; 2.1.2 Generic Modeling Environment; 2.2 COMPONENT COMPOSITION FRAMEWORK; 2.3 REFLECTION AND INTROSPECTION (R-I); 2.4 SYSTEMC; 2.5 MODEL-DRIVEN VALIDATION; 2.5.1 Microprocessor Validation Flow; 2.5.2 Simulation-Based Functional Validation.…”
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Dermatologic principles and practice in oncology : conditions of the skin, hair, and nails in cancer patients

Table of Contents: “…Ito Section 5 Late Cutaneous Events from Cancer Treatments -- 32 Late Dermatologic Conditions / Jennifer Namchoi Section 6 Dermatologic Practice in Oncology 33 Management Algorithms for Dermatologic Adverse Events / Alyx Rosen, Iris Amitay-Laish and Mario E. …”
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Haptic Feedback Teleoperation of Optical Tweezers by Ni, Zhenjiang

Table of Contents: “…Position detection devices; 3.2.2. Candidate algorithms.…”
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Atlas of minimally invasive surgery for lung and esophageal cancer

Table of Contents: “…2.2.5.1 Cardiac Risk Scoring Systems2.2.5.2 Cardiopulmonary Risk Algorithms; 2.2.6 Preoperative Risk Reduction; 2.2.6.1 Smoking; 2.2.6.2 Preoperative Physical Rehabilitation; 2.2.6.3 Frailty; Conclusions; 2.3 Staging and Selection of Patients for Minimally Invasive Lung Cancer Resection; 2.3.1 Introduction; 2.3.2 Staging; 2.3.2.1 Radiographic Staging; 2.3.2.2 Pathologic Staging; 2.3.3 Patient Selection; 2.3.3.1 Operability: Assessment of Cardiopulmonary Fitness; 2.3.3.2 Resectability: Tumor Characteristics; 2.4 Type and Conduction of the Anaesthesia; 2.4.1 Introduction.…”
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Deterministic Network Calculus. by Bouillard, Anne

Table of Contents: “…Summary; PART 1: (min, plus) Functions and Algorithms; 2. The (min, plus) Functions Semi-ring; 2.1. …”
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Towards Cognitive Autonomous Networks : Network Management Automation for 5G and Beyond. by Mwanje, Stephen S.

Table of Contents: “…Cover -- Title Page -- Copyright -- Contents -- List of Contributors -- Foreword I -- Foreword II -- Preface -- Chapter 1 The Need for Cognitive Autonomy in Communication Networks -- 1.1 Complexity in Communication Networks -- 1.1.1 The Network as a Graph -- 1.1.2 Planes, Layers, and Cross-Functional Design -- 1.1.3 New Network Technology -- 5G -- 1.1.4 Processes, Algorithms, and Automation -- 1.1.5 Network State Changes and Transitions -- 1.1.6 Multi-RAT Deployments -- 1.2 Cognition in Network Management Automation -- 1.2.1 Business, Service and Network Management Systems…”
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Optimization of Energy Systems. by Dincer, Ibrahim

Table of Contents: “…2.2.5 Combustion Chamber (CC)2.2.6 Ejector; 2.2.7 Flat Plate Solar Collector; 2.2.8 Solar Photovoltaic Thermal (PV/T) System; 2.2.9 Solar Photovoltaic Panel; 2.3 Optimization; 2.3.1 System Boundaries; 2.3.2 Objective Functions and System Criteria; 2.3.3 Decision Variables; 2.3.4 Constraints; 2.3.5 Optimization Methods; 2.3.5.1 Classical Optimization; 2.3.5.2 Numerical Optimization Methods; 2.3.5.3 Evolutionary Algorithms; 2.4 Multi-objective Optimization; 2.4.1 Sample Applications of Multi-objective Optimization; 2.4.1.1 Economics; 2.4.1.2 Finance; 2.4.1.3 Engineering.…”
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Relationship inference with Familias and R : statistical methods in forensic genetics by Egeland, Thore, Kling, Daniel, Mostad, Petter, 1964-

Table of Contents: “…4.1.3 Generalization and the Lander-Green Algorithm4.1.4 Extensions; X-chromosomal markers; Mutations; Subpopulation correction; Dropouts and silent alleles; 4.2 Linkage Disequilibrium; 4.2.1 Introduction to Calculations; 4.2.2 *Generalization; Cluster approach; Exact calculations; 4.3 Haplotype Frequency Estimation; 4.4 Programs for Linked Markers; 4.4.1 FamLink; 4.4.2 FamLinkX; 4.5 Exercises; 4.5.1 Autosomal Markers and FamLink; 4.5.2 X-Chromosomal Markers and FamLinkX; Chapter 5: Relationship inference with R; 5.1 Using R; 5.1.1 R Packages for Relationship Inference…”
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A Polygeneration Process Concept for Hybrid Solar and Biomass Power Plant : Simulation, Modeling, and Optimization. by Sahoo, Umakanta

Table of Contents: “…6.3 Primary Energy Savings on the Polygeneration Process in an HSB Thermal Power Plant6.4 Optimization; 6.4.1 Objective Functions; 6.4.2 Decision Variable and Constraints; 6.4.3 Genetic Algorithm (GA); 6.5 Cost Analysis; 6.6 Analysis Of Polygeneration Process in an HSB Thermal Power Plant for Power, Cooling, and Desalination; 6.7 Optimization of the Polygeneration System; 6.8 Cost Analysis of a Polygeneration System; Exercise; References; Appendix 1; Nomenclature; Greek; Subscripts; Acronyms; Appendix 2; EES Software Coding; Appendix 3; Multiple Choice Questions (MCQ) with Answers; Answers.…”
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Stochastic filtering with applications in finance by Bhar, Ramaprasad

Table of Contents: “…Background to particle filter for non Gaussian problems. 1.8. Particle filter algorithm. 1.9. Unobserved component models. 1.10. …”
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3D face modeling, analysis and recognition by Daoudi, Mohamed, Ph. D., Srivastava, Anuj, Veltkamp, Remco C., 1963-

Table of Contents: “…4 3D Morphable Models for Face Surface Analysis and Recognition4.1 Introduction; 4.2 Data Sets; 4.3 Face Model Fitting; 4.3.1 Distance Measure; 4.3.2 Iterative Face Fitting; 4.3.3 Coarse Fitting; 4.3.4 Fine Fitting; 4.3.5 Multiple Components; 4.3.6 Results; 4.4 Dynamic Model Expansion; 4.4.1 Bootstrapping Algorithm; 4.4.2 Results; 4.5 Face Matching; 4.5.1 Comparison; 4.5.2 Results; 4.6 Concluding Remarks; Exercises; References; 5 Applications; 5.1 Introduction; 5.2 3D Face Databases; 5.3 3D Face Recognition; 5.3.1 Challenges of 3D Face Recognition; 5.3.2 3D Face Recognition: State of the Art.…”
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Energy storage for sustainable microgrid by Gao, David Wenzhong

Table of Contents: “…1.2.4.2 Weighted Least Squares Estimation1.2.4.3 Newton-Raphson Algorithm; 1.3 Microgrid Control Methods; 1.3.1 PQ Control; 1.3.2 V/f Control; 1.3.3 Droop Control; 1.3.3.1 Active Power Control; 1.3.3.2 Voltage Control; 1.4 Control Architectures in Microgrids; 1.4.1 Master-Slave Control; 1.4.2 Peer-to-peer Control; 1.4.3 Hierarchy Control; 1.5 Microgrid Protection; 1.6 Three-Phase Circuit for Grid-Connected DG; 1.6.1 LC Filter; 1.6.2 Isolation Transformer; 1.7 Energy Storage Technology in Renewable Microgrids; 1.7.1 Batteries; 1.7.1.1 Lead-Acid Batteries; 1.7.1.2 Lithium-Ion Batteries.…”
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Introduction to OFDM receiver design and simulation by Liu, Y. J.

Table of Contents: “…References-7 Error-Correcting Codes and Interleaver-7.1 Introduction-7.2 Linear Block Codes-7.2.1 Generator Matrix-7.2.2 Parity Check Matrix-7.2.3 Syndrome-7.2.4 Error Correction-7.2.5 Hamming Codes-7.3 Cyclic Codes-7.3.1 Generator Polynomial-7.3.2 Syndrome Polynomial-7.4 Convolutional Code-7.4.1 Convolutional Encoder-7.4.2 Convolutional Decoder and Viterbi Algorithm-7.4.3 Convolutional Code in the IEEE 802.11a-7.4.4 Punctured Convolutional Codes-7.5 Interleaver-7.5.1 Illustration of an Interleaver-7.5.2 Interleaver Used in the IEEE 802.11a…”
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