Tabla de Contenidos: “…4.6 Condiciones en la frontera para campos electrostáticos -- 4.6.1 Dieléctrico-dieléctrico -- 4.6.2 Dieléctrico-conductor -- 4.6.3 Conductor-conductor -- 4.6.4 Conductor-espacio libre (vacío) -- 4.7 Problemas electrostáticos con valores de frontera -- 4.7.1 Ecuaciones de Poisson y Laplace -- 4.7.2 Teorema de unicidad -- 4.7.3 Aplicación de las ecuaciones de Poisson y Laplace -- 4.8 Resistencia y capacitancia -- 5 Magnetostática -- Introducción -- 5.1 Fuerza magnética y fuerza electromagnética -- 5.2 Ecuaciones fundamentales de la magnetostática en el espacio libre -- 5.3 Potencial magnético vector -- 5.4 Ley de Biot-Savart -- 5.5 Fuerza magnética sobre un conductor que transporta una corriente -- 5.6 Fuerza magnética entre dos circuitos -- 5.7 Momento de torsión sobre una espira que lleva una corriente -- 5.7.1 Campo magnético paralelo al plano de la espira -- 5.7.2 Campo magnético perpendicular al plano de la espira -- 5.8 Dipolo magnético -- 5.9 Inductancia e inductores -- 5.10 Energía magnética -- 5.10.1 Energía magnética en función de B y H -- 6 Magnetostática en medios materiales -- Introducción -- 6.1 Tipos de materiales magnéticos -- 6.2 Magnetización de materiales -- 6.2.1 Momento angular orbital y de espín -- 6.3 Intensidad de campo magnético y permeabilidad relativa -- 6.4 Histéresis de los materiales ferromagnéticos -- 6.5 Condiciones en la frontera magnetostática -- Bibliografía -- A Convención de suma de Einstein -- A.1 Índices repetidos -- A.2 Índices libres y mudos -- A.3 Doble suma -- A.4 Sustitución -- A.5 Delta Kronecker -- B Fórmulas vectoriales -- B.1 Identidades del álgebra vectorial -- B.2 Identidades del análisis vectorial -- B.3 Identidades especiales -- C Función delta de Dirac -- C.1 Función delta de Dirac -- C.2 Propiedades -- Índice alfabético…”

Tabla de Contenidos: “…1.9 SUMMARY AND A LOOK AHEADExercises; Interview Questions; Chapter 2 Combinational Logic Design; 2.1 INTRODUCTION; 2.2 BOOLEAN EQUATIONS; 2.2.1 Terminology; 2.2.2 Sum-of-Products Form; 2.2.3 Product-of-Sums Form; 2.3 BOOLEAN ALGEBRA; 2.3.1 Axioms; 2.3.2 Theorems of One Variable; 2.3.3 Theorems of Several Variables; 2.3.4 The Truth Behind It All; 2.3.5 Simplifying Equations; 2.4 FROM LOGIC TO GATES; 2.5 MULTILEVEL COMBINATIONAL LOGIC; 2.5.1 Hardware Reduction; 2.5.2 Bubble Pushing; 2.6 X'S AND Z'S, OH MY; 2.6.1 Illegal Value: X; 2.6.2 Floating Value: Z; 2.7 KARNAUGH MAPS…”

Tabla de Contenidos: “…Introducing Petri Nets; 5.1 About Petri Nets; 5.1.1 Petri Graphs and Petri Nets; 5.1.2 Enabling and Firing; 5.1.3 Another Definition of Petri Nets; 5.2 About Languages; 5.3 About PETRIFY; 5.4 Illustrating Petri Nets; 5.5 Labeled Nets; 5.6 Bounded Nets; 5.7 Observation Equivalence of LPNs; 5.8 From Blot to Petri Nets; 5.9 Liveness and Persistence; 5.10 Simple Reduction Rules; 5.11 Marked Graphs; 5.12 A Simple Net Algebra; 5.12.1 The Prefix Operator; 5.12.2 The Choice Operator; 5.12.3 The Star Operator; 5.12.4 Parallel Compositions…”

Tabla de Contenidos: “…Chapter 5: Finite volume method -- 5.1 General Concept -- 5.2 FVM Application Details -- 5.2.1 Step by step application of the FVM -- 5.2.2 Surface and volume integrals -- 5.2.3 Discretization of convective fluxes -- 5.2.4 Discretization of diffusive fluxes -- 5.2.5 Evaluation of the time derivative -- 5.2.6 Boundary conditions -- 5.2.7 Solving algebraic system of equations -- 5.3 Example of Advection-Diffusion Equation in 1D -- 5.3.1 Constant unknown function -- 5.3.2 Linear variation approximation of the unknown function -- 5.3.3 Parabolic variation approximation of the unknown function -- 5.3.4 Error of the approximation -- Chapter 6: Properties of numerical methods -- 6.1 Properties of Numerical Methods -- 6.1.1 Convergence -- 6.1.2 Consistency -- 6.1.3 Stability -- 6.1.4 Lax's theorem of equivalence -- 6.2 Convergence of FDM Schemes -- 6.2.1 Convergence for ODEs -- 6.2.2 Convergence for PDEs -- 6.2.3 Amplitude and phase errors -- 6.3 Convergence of FVM Schemes -- 6.3.1 Convective fluxes -- 6.3.2 Diffusive fluxes -- 6.4 Examples -- 6.4.1 Stability region of a simple ODE -- 6.4.2 Convergence of an ODE: Emptying of a groundwater reservoir -- 6.4.3 PDE: Convergence analysis for Preissmann scheme applied to advection equation -- 6.4.4 PDE: Convergence analysis for diffusion equation -- Chapter 7: River system modelling and flood propagation -- 7.1 Introduction -- 7.2 River Systems Modelling -- 7.2.1 Preissmann solution -- 7.2.2 Abbott-Ionescu solution -- 7.2.3 Initial and boundary conditions -- 7.2.4 River networks -- 7.3 Modelling Floods -- 7.4 River Routing Example -- Chapter 8: Water quality modelling -- 8.1 Introduction -- 8.2 Processes Described in Water Quality Models -- 8.3 River Water Quality Models -- 8.4 Lakes Water Quality Modelling -- 8.5 Examples of Lake Hydrodynamics and Water Quality Models -- 8.5.1 Sontea-Fortuna wetland system…”

Tabla de Contenidos: “…6.4 AIC Criterion -- 6.5 MDL Criterion -- 6.6 Durbin-Levinson Algorithm -- 7 Identification of State Space Models -- 7.1 Introduction -- 7.2 Hankel Matrix -- 7.3 Order Determination -- 7.4 Determination of Matrices and -- 7.5 Determination of Matrix -- 7.6 Mid Summary: An Ideal Procedure -- 7.7 Order Determination with SVD -- 7.8 Reliable Identification of a State Space Model -- 8 Predictive Control -- 8.1 Introduction -- 8.2 Minimum Variance Control -- 8.3 Generalized Minimum Variance Control -- 8.4 Model‐Based Predictive Control -- 8.5 Data‐Driven Control Synthesis -- 9 Kalman Filtering and Prediction -- 9.1 Introduction -- 9.2 Kalman Approach to Prediction and Filtering Problems -- 9.3 The Bayes Estimation Problem -- 9.4 One‐step‐ahead Kalman Predictor -- 9.5 Multistep Optimal Predictor -- 9.6 Optimal Filter -- 9.7 Steady‐State Predictor -- 9.8 Innovation Representation -- 9.9 Innovation Representation Versus Canonical Representation -- 9.10 K‐Theory Versus K-W Theory -- 9.11 Extended Kalman Filter - EKF -- 9.12 The Robust Approach to Filtering -- 10 Parameter Identification in a Given Model -- 10.1 Introduction -- 10.2 Kalman Filter‐Based Approaches -- 10.3 Two‐Stage Method -- 11 Case Studies -- 11.1 Introduction -- 11.2 Kobe Earthquake Data Analysis -- 11.3 Estimation of a Sinusoid in Noise -- Appendix A: Linear Dynamical Systems -- A.1 State Space and Input-Output Models -- A.2 Lagrange Formula -- A.3 Stability -- A.4 Impulse Response -- A.5 Frequency Response -- A.6 Multiplicity of State Space Models -- A.7 Reachability and Observability -- A.8 System Decomposition -- A.9 Stabilizability and Detectability -- Appendix B: Matrices -- B.1 Basics -- B.2 Eigenvalues -- B.3 Determinant and Inverse -- B.4 Rank -- B.5 Annihilating Polynomial -- B.6 Algebraic and Geometric Multiplicity -- B.7 Range and Null Space -- B.8 Quadratic Forms…”

Tabla de Contenidos: “…Single-Sample Identification -- Multifeature Pattern Recognition -- Summary -- References -- Problems -- Chapter 11 Fuzzy Control Systems -- Control System Design Problem -- Control (Decision) Surface -- Assumptions in a Fuzzy Control System Design -- Simple Fuzzy Logic Controllers -- Examples of Fuzzy Control System Design -- Aircraft Landing Control Problem -- Fuzzy Engineering Process Control -- Classical Feedback Control -- Classical PID Control -- Fuzzy Control -- Multi-Input, Multi-Output (MIMO) Control Systems -- Fuzzy Statistical Process Control -- Measurement Data: Traditional SPC -- Plant Simulation -- Establishing Fuzzy Membership Values -- Attribute Data: Traditional SPC -- Industrial Applications -- Summary -- References -- Problems -- Chapter 12 Applications of Fuzzy Systems Using Miscellaneous Models -- Fuzzy Optimization -- One-Dimensional Optimization -- Fuzzy Cognitive Mapping -- Concept Variables and Causal Relations -- Paths and Cycles -- Indirect Effect -- Total Effect -- Indeterminacy -- Fuzzy Cognitive Maps -- Adjacency Matrix -- Threshold Function -- Feedback -- Min-Max Inference Approach -- Genetically Evolved Fuzzy Cognitive Maps -- Agent-Based Models -- Fuzzy Arithmetic and the Extension Principle -- Extension Principle -- Crisp Functions, Mapping, and Relations -- Functions of Fuzzy Sets: Extension Principle -- Fuzzy Algebra -- Fuzzy Arithmetic -- Data Fusion -- Kalman Filter in Data Fusion -- Summary -- References -- Problems -- Chapter 13 Monotone Measures: Belief, Plausibility, Probability, and Possibility -- Monotone Measures -- Belief and Plausibility -- Evidence Theory -- Probability Measures -- Possibility and Necessity Measures -- Possibility Distributions as Fuzzy Sets -- Possibility Distributions Derived from Empirical Intervals -- Deriving Possibility Distributions from Overlapping Intervals…”

Tabla de Contenidos: “…2.1.5 2's complement2.1.6 Signed numbers; 2.1.7 Subtraction and multiplication; 2.1.8 Binary coded decimal; 2.1.9 Gray code; 2.1.10 ASCII code; 2.1.11 Boolean algebra; 2.1.12 Digital logic circuits; 2.1.13 Review questions; 2.1.14 Activities; Chapter 2.2. …”

Tabla de Contenidos: “…-- Im Terminal navigieren -- Ein Programm auf den Arduino übertragen -- Den Code kompilieren -- Linken -- Upload -- AVR-Programmieren -- Quellcode vom Arduino auf AVR anpassen -- Boolesche Algebra -- Zusammenfassung -- Ein paar Fragen ... -- ... und ein paar Aufgaben -- Kapitel 10: Git - Schatztruhe für deinen Code -- Unser Beispielsketch -- Versionskontrolle mit Git -- Der Unterschied zwischen Commits und Änderungen -- Weiter geht es mit unserem Repository -- Teilen deines Codes im Internet -- Deinen Code dokumentieren -- Zusammenfassung -- Ein paar Fragen ... -- ... und ein paar Aufgaben -- Kapitel 11:1 Quellcode anderer Entwickler lesen -- Die Dokumentation -- Der mysteriöse Quellcode -- Zusammenfassung -- Ein paar Fragen ... -- ... und eine Aufgabe -- Kapitel 12: Vergiss mein nicht - Nutzung des EEPROM -- Allgemeines zum EEPROM -- Was könnte man mit dem EEPROM programmieren? …”

Tabla de Contenidos: “…SYNTHESIS OF ARITHMETIC CIRCUITS; CONTENTS; Preface; About the Authors; 1 Introduction; 1.1 Number Representation; 1.2 Algorithms; 1.3 Hardware Platforms; 1.4 Hardware-Software Partitioning; 1.5 Software Generation; 1.6 Synthesis; 1.7 A First Example; 1.7.1 Specification; 1.7.2 Number Representation; 1.7.3 Algorithms; 1.7.4 Hardware Platform; 1.7.5 Hardware-Software Partitioning; 1.7.6 Program Generation; 1.7.7 Synthesis; 1.7.8 Prototype; 1.8 Bibliography; 2 Mathematical Background; 2.1 Number Theory; 2.1.1 Basic Definitions; 2.1.2 Euclidean Algorithms; 2.1.3 Congruences; 2.2 Algebra…”

Tabla de Contenidos: “…5.2.2 OR5.2.3 NOT; 5.2.4 NAND; 5.2.5 NOR; 5.2.6 Exclusive OR (XOR); 5.3 Latching; 5.4 Multiple outputs; 5.5 Entering programs; 5.5.1 Ladder symbols; 5.6 Function blocks; 5.6.1 Logic gates; 5.6.2 Boolean algebra; 5.7 Program examples; 5.7.1 Location of stop switches; Problems; 6 IL, SFC and ST programming methods; 6.1 Instruction lists; 6.1.1 Ladder programs and instruction lists; 6.1.2 Branch codes; 6.1.3 More than one rung; 6.1.4 Programming examples; 6.2 Sequential function charts; 6.2.1 Branching and convergence; 6.2.2 Actions; 6.3 Structured text; 6.3.1 Conditional statements…”

Tabla de Contenidos: “…3.2.7 Views: Virtual Tables3.2.8 The System Catalog; 3.3 The Integrity Component; 3.3.1 Primary Keys; 3.3.2 Foreign Keys; 3.3.3 Constraints; 3.3.4 Null Values; 3.4 Normalization; 3.4.1 Normal Forms; 3.4.2 First Normal Form; 3.4.3 Functional Dependencies; 3.4.4 Second Normal Form; 3.4.5 Third Normal Form; 3.5 The Manipulative Component; 3.5.1 Relational Algebra and Calculus; 3.5.2 The Relational Query Language; 3.5.3 The Advent of SQL; 3.6 The Meaning of Relational; 3.7 Summary; 4 Everything You Ever Wanted to Know about SQL but Were Afraid to Ask; 4.1 The Relational Model…”

Tabla de Contenidos: “….); 4.3 Interpolation; 4.3.1 Linear interpolation; 4.3.2 Loglinear interpolation; 4.3.3 Linear on zero interpolation; 4.3.4 Cubic spline interpolation; 4.4 Root finding; 4.4.1 Bisection method; 4.4.2 Newton-Raphson method; 4.5 Linear algebra; 4.5.1 Matrix multiplication; 4.5.2 Matrix inversion; 4.5.3 Matrix pseudo-inverse…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright and Credits -- Dedication -- Packt Upsell -- Contributors -- Table of Contents -- Preface -- Chapter 1: The Declarative Programming Style -- Technical requirements -- Principles of declarative programming -- Example - go-to versus loops -- Example - nested loop -- Don't Repeat Yourself (DRY) -- Declarative versus imperative collections -- Filtering -- Declarative programming in other languages -- Summary -- Questions -- Chapter 2: Functions and Lambdas -- Functions as behavior -- Functions in functional programming -- Higher-order functions -- Understanding lambda functions -- The concept of functions in different programming languages -- Summary -- Questions -- Chapter 3: Functional Data Structures -- Collections framework -- Imperative collections -- Functional collections -- Algebraic approach -- Effect types -- Try -- Option -- Data structures in different programming languages -- Summary -- Questions -- Further reading -- Chapter 4: The Problem of Side Effects -- Side effects -- Mutable states -- Pure functions -- Referential transparency -- Generally encountered side effects -- Error -- Absence of result -- Delay and asynchronous computations -- Logging -- Input-output operations -- But how do we get rid of the side effects? …”

Tabla de Contenidos: “…Log-Linear Models for Categorical Variables -- Regression Models for Categorical Variables -- Models for Event Histories -- Models for Multiple-Item Measurement -- Nonlinear, Nonadditive Models -- Geometric and Algebraic Models -- Scaling -- Ordered Factorial Systems -- Clustering -- Network Models -- STATISTICAL INFERENCE AND ANALYSIS -- Causal Inference -- New Statistical Techniques -- Internal Resampling -- Robust Techniques -- Many Interrelated Parameters -- Missing Data -- Computing -- Computer Packages and Expert Systems -- Exploratory Analysis and Graphic Presentation -- Combining Evidence -- OPPORTUNITIES AND NEEDS -- 6 The Research Support System -- HUMAN RESOURCES -- Colleges and Graduate Schools -- Undergraduate Education -- Graduate Education -- Postdoctoral Training and Collaboration -- Postdoctoral Fellowships and Traineeships -- Advanced Training Institutes -- Collaboration and Communication -- TECHNOLOGICAL RESOURCES -- Computers -- Neuroimaging Devices -- Animal Care -- DATA RESOURCES -- Large-Scale Data Bases -- Research Access to Government Data -- Corporate and Local Government Archives -- FUNDING RESOURCES -- Modes of Support -- Grant Size and Duration -- The Disciplines and Interdisciplinary Research -- Interdisciplinary Research Centers -- THE PROBLEM OF VOICE -- 7 Raising the Scientific Yield -- RESEARCH FRONTIERS -- Behavior, Mind, and Brain -- Motivational and Social Contexts of Behavior -- Choice and Allocation -- Institutions and Cultures -- Methods of Data Collection, Representation, and Analysis -- RECOMMENDED NEW RESOURCES -- Human Resources -- Technological Resources -- Data Resources -- Interdisciplinary Research Centers -- Investigator-Initiated Grants -- Research Agency Changes -- CONCLUSION -- Appendix A Trends in Support for Research in the Behavioral and Social Sciences -- FEDERAL SUPPORT…”

“…El libro asume del lector un conocimiento previo de cálculo diferencial, integral, vectorial y álgebra lineal. En la primera parte se abordan temas como la teoría de funciones de variable compleja, la teoría de distribuciones, el análisis de Fourier, la transformada de Laplace y el estudio de las principales ecuaciones diferenciales de la Física. …”

Tabla de Contenidos: “…-- Advantages over traditional shallow methods -- Impact of deep learning -- The motivation of deep architecture -- The neural viewpoint -- The representation viewpoint -- Distributed feature representation -- Hierarchical feature representation -- Applications -- Lucrative applications -- Success stories -- Deep learning for business -- Future potential and challenges -- Summary -- Chapter 2: Getting Yourself Ready for Deep Learning -- Basics of linear algebra -- Data representation -- Data operations -- Matrix properties -- Deep learning with GPU -- Deep learning hardware guide -- CPU cores -- RAM size -- Hard drive -- Cooling systems -- Deep learning software frameworks -- TensorFlow - a deep learning library -- Caffe -- MXNet -- Torch -- Theano -- Microsoft Cognitive Toolkit -- Keras -- Framework comparison -- Setting up deep learning on AWS -- Setup from scratch -- Setup using Docker -- Summary -- Chapter 3: Getting Started with Neural Networks -- Multilayer perceptrons -- The input layer -- The output layer -- Hidden layers -- Activation functions -- Sigmoid or logistic function -- Tanh or hyperbolic tangent function -- ReLU -- Leaky ReLU and maxout -- Softmax -- Choosing the right activation function -- How a network learns -- Weight initialization -- Forward propagation -- Backpropagation -- Calculating errors -- Backpropagation -- Updating the network -- Automatic differentiation -- Vanishing and exploding gradients -- Optimization algorithms -- Regularization -- Deep learning models -- Convolutional Neural Networks -- Convolution -- Pooling/subsampling -- Fully connected layer -- Overall…”

Tabla de Contenidos: “…. -- Figure 4.5 Using consumer-grade eye tracker (left) to monitor visual attention while students interact with Guru (right) in classrooms -- Figure 4.6 Sample video (left) in the Algebra Nation platform along with a self-report engagement questionnaire (right) -- Figure 4.7 Organisation of activities with respect to expected engagement and learning (from left to higher) as per the ICAP framework -- Figure 4.8 Example of a problem and pendulum solution in Physics Playground -- Figure 4.9 GazeTutor interface with animated agent (0), image panel (1), and input box (2). …”

Tabla de Contenidos: “…11 -- 2 Polish Up Your Algebra Skills 13 -- Walk the Line: Linear Equations 14 -- Common Forms of Linear Equations 14 -- Calculating Slope 16 -- Interpreting Linear Graphs 18 -- You've Got the Power: Exponential Rules 21 -- Breaking Up Is Hard to Do: Factoring Polynomials 22 -- Greatest Common Factor 23 -- Special Factoring Patterns 23 -- Solving Quadratic Equations 24 -- Method One: Factoring 25 -- Method Two: Completing the Square 25 -- Method Three: The Quadratic Formula 26 -- Synthesizing the Quadratic Solution Methods 27 -- 3 Equations, Relations, and Functions 31 -- What Makes a Function Tick? …”

“…Linear filtering methods originate in stochastic processes, while subspace methods have largely been based on developments in numerical linear algebra and matrix approximation theory. This book bridges the gap between the…”

“…Additionally, basic knowledge in linear algebra and calculus is desired. What You Will Learn Implement different neural network models in Python Select the best Python framework for deep learning such as PyTorch, Tensorflow, MXNet and Keras Apply tips and tricks related to neural networks internals, to boost learning performances Consolidate machine learning principles and apply them in the deep learning field Reuse and adapt Python code snippets to everyday problems Evaluate the cost/benefits and performance implication of each discussed solution In Detail Deep Learning is revolutionizing a wide range of industries. …”