Tabla de Contenidos: “…Lista bloccata vs lista aperta: l'insoddisfacente approdo della Consulta. 166 -- 5.2. …”

Tabla de Contenidos: “…Cover -- Copyright -- Contents -- About the author -- Preface -- Chapter 1: Modelling theory -- 1.1 Context and Nature of Modelling -- 1.1.1 Classification of models -- 1.1.2 Computational Hydraulics -- 1.2 Conceptualiation: Building a Model -- 1.3 Mathematical Modelling in Practice -- 1.3.1 Selecting a proper model -- 1.3.2 Testing a model -- 1.4 Development and Application of Models -- Chapter 2: Modelling water related problems -- 2.1 Basic Conservation Equations -- 2.1.1 Conservation of mass -- 2.1.2 Conservation of momentum -- 2.1.3 Conservation of energy -- 2.2 Mathematical Classification of Flow Equations -- 2.2.1 Solutions of ODE -- 2.2.2 Solutions of PDE -- 2.3 Navier-Stokes and Saint-Venant Equations -- 2.3.1 Navier-Stokes equations -- 2.3.2 Saint-Venant equations -- 2.3.3 Characteristic form of Saint-Venant equations -- Chapter 3: Discretization of the fluid flow domain -- 3.1 Discrete Solutions of Equations -- 3.2 Space Discretization -- 3.2.1 Structured grids -- 3.2.2 Unstructured grids -- 3.2.3 Grid generation -- 3.2.4 Physical aspects of space discretization -- 3.3 Time Discretization -- Chapter 4: Finite difference method -- 4.1 General Concepts -- 4.2 Approximation of the First Order Derrivative -- 4.3 Approximation of Higher Order Derrivatives -- 4.4 Finite Differences for Ordinary Differential Equations -- 4.4.1 Problem position -- 4.4.2 Explicit schemes (Euler method) -- 4.4.3 Implicit schemes (Improved Euler method) -- 4.4.4 Mixed schemes -- 4.4.5 Weighted averaged schemes -- 4.4.6 Runge-Kutta methods -- 4.5 Numerical Schemes for Partial Differential Equations -- 4.5.1 Principle of FDM for PDEs -- 4.5.2 Hyperbolic PDEs -- 4.5.3 Parabolic PDEs -- 4.5.4 Elliptic PDEs -- 4.6 Examples -- 4.6.1 ODE: Solution of the linear reservoir problem -- 4.6.2 PDE: Simple wave propagation -- 4.6.3 PDE: Diffusion equation…”

Tabla de Contenidos: “…Parameter Analysis on Blur, CLAHE, and CANNY Filters -- Modeling and Development -- Analysis -- Iris Recognition (2) -- Modeling and Development -- Conclusions and Problems -- "Average Color" Recognition -- Modeling and Development -- Conclusions -- Project Analysis -- Data Analysis -- Precision -- Recall -- F-measure -- Result -- Video #1 -- Video #2 -- Video #3 -- Video #4 -- Project Conclusions -- Summary -- Chapter 3: Developing a Video Game -- Roles in the Video Game Industry -- Producers -- Publishers -- Game Developers -- Roles and Processes of Game Development -- Game Design -- Game Art Design -- Game Programming -- Game Testing -- Software Development -- Game Development Phases -- Pre-Production Phase -- Outsourcing -- Production Phase -- Milestones: The Cornerstones of Development -- Post-Production Phase -- Localization -- Fan Translation -- Summary -- Chapter 4: Turning Points in Game Development -- Game Engines -- Rendering Engine -- Indie Video Games -- Crowdfunding -- The Case of Dreams: Developing a Game Within a Video Game -- Current Problems in the Development of Video Games -- Crunch Time -- Piracy -- Programming Stages -- Paradigms and Programming Languages -- Visual Programming -- Summary -- Chapter 5: Developing a Game in Python -- Python and Pygame -- Designing the Video Game -- Development Team -- Game Design Document and Production -- Game Menu -- Short Introduction to Pygame -- Game Interface -- The Player -- Powering Up -- The Enemies -- The Bosses -- Collision Management -- The Levels -- Summary -- Chapter 6: Game Development - Industry Standards -- Game Terminology -- Overall Design of the Game -- Frontend and Backend in Game Development -- Verify the Token -- General Description of the Game's Services -- Network Interfaces and Sequence Diagram for the Game Development Cycle -- Game Network Interfaces -- Sequence Diagrams…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright Page -- About the Author -- About the Technical Editor -- Acknowledgments -- Contents at a Glance -- Contents -- Introduction -- Who I Am and Why I'm Writing About This Topic -- Who This Book Is For -- Why You Should Learn SQL if You Want to Be a Data Scientist -- What I Hope You Gain from This Book -- Conventions -- Reader Support for This Book -- Companion Download Files -- How to Contact the Publisher -- How to Contact the Author -- Chapter 1 Data Sources -- Data Sources -- Tools for Connecting to Data Sources and Editing SQL -- Relational Databases -- Dimensional Data Warehouses -- Asking Questions About the Data Source -- Introduction to the Farmer's Market Database -- A Note on Machine Learning Dataset Terminology -- Exercises -- Chapter 2 The SELECT Statement -- The SELECT Statement -- The Fundamental Syntax Structure of a SELECT Query -- Selecting Columns and Limiting the Number of Rows Returned -- The ORDER BY Clause: Sorting Results -- Introduction to Simple Inline Calculations -- More Inline Calculation Examples: Rounding -- More Inline Calculation Examples: Concatenating Strings -- Evaluating Query Output -- SELECT Statement Summary -- Exercises Using the Included Database -- Chapter 3 The WHERE Clause -- The WHERE Clause -- Filtering SELECT Statement Results -- Filtering on Multiple Conditions -- Multi-Column Conditional Filtering -- More Ways to Filter -- BETWEEN -- IN -- LIKE -- IS NULL -- A Warning About Null Comparisons -- Filtering Using Subqueries -- Exercises Using the Included Database -- Chapter 4 CASE Statements -- CASE Statement Syntax -- Creating Binary Flags Using CASE -- Grouping or Binning Continuous Values Using CASE -- Categorical Encoding Using CASE -- CASE Statement Summary -- Exercises Using the Included Database -- Chapter 5 SQL JOINs -- Database Relationships and SQL JOINs -- A Common Pitfall when Filtering Joined Data -- JOINs with More than Two Tables -- Exercises Using the Included Database -- Chapter 6 Aggregating Results for Analysis -- GROUP BY Syntax -- Displaying Group Summaries -- Performing Calculations Inside Aggregate Functions -- MIN and MAX -- COUNT and COUNT DISTINCT -- Average -- Filtering with HAVING -- CASE Statements Inside Aggregate Functions -- Exercises Using the Included Database -- Chapter 7 Window Functions and Subqueries -- ROW NUMBER -- RANK and DENSE RANK -- NTILE -- Aggregate Window Functions -- LAG and LEAD -- Exercises Using the Included Database -- Chapter 8 Date and Time Functions -- Setting datetime Field Values -- EXTRACT and DATE_PART -- DATE_ADD and DATE_SUB -- DATEDIFF -- TIMESTAMPDIFF -- Date Functions in Aggregate Summaries and Window Functions -- Exercises -- Chapter 9 Exploratory Data Analysis with SQL -- Demonstrating Exploratory Data Analysis with SQL -- Exploring the Products Table -- Exploring Possible Column Values -- Exploring Changes Over Time -- Exploring Multiple Tables Simultaneously -- Exploring Inventory vs. …”

Tabla de Contenidos: “…Preparación y respuesta al desastre en Colombia -- Preparación y respuesta efectiva al desastre: Aspectos claves de la gestión del riesgo de desastres en Colombia -- Roles y responsabilidades -- Sistemas de alerta temprana -- Planeamiento de respuesta a emergencias -- Ejercicios de manejo de crisis y simulacros -- Mecanismos de coordinación para una respuesta efectiva y oportuna al desastre -- Mecanismos de mejoramiento continuo en la respuesta a los desastres -- Notas -- Referencias…”

Tabla de Contenidos: “…Statutory income tax progressivity around the income level of the average production ... -- 3.2.3. Trade-offs between equity and efficiency -- 3.3. …”

Tabla de Contenidos: “…-- A very high level overview of machine learning -- A brief history of the development of machine learning algorithms -- Generalizing with data -- Overfitting, underfitting and the bias-variance tradeoff -- Avoid overfitting with cross-validation -- Avoid overfitting with regularization -- Avoid overfitting with feature selection and dimensionality reduction -- Preprocessing, exploration, and feature engineering -- Missing values -- Label encoding -- One-hot-encoding -- Scaling -- Polynomial features -- Power transformations -- Binning -- Combining models -- Bagging -- Boosting -- Stacking -- Blending -- Voting and averaging -- Installing software and setting up -- Troubleshooting and asking for help -- Summary -- Chapter 2: Exploring the 20 Newsgroups Dataset with Text Analysis Algorithms -- What is NLP? …”

Tabla de Contenidos: “…Front Cover -- Temporal Data Mining via Unsupervised Ensemble Learning -- Temporal Data Mining via Unsupervised Ensemble Learning -- Copyright -- Contents -- List of Figures -- List of Tables -- Acknowledgments -- 1 - Introduction -- 1.1 BACKGROUND -- 1.2 PROBLEM STATEMENT -- 1.3 OBJECTIVE OF BOOK -- 1.4 OVERVIEW OF BOOK -- 2 - Temporal Data Mining -- 2.1 INTRODUCTION -- 2.2 REPRESENTATIONS OF TEMPORAL DATA -- 2.2.1 TIME DOMAIN-BASED REPRESENTATIONS -- 2.2.2 TRANSFORMATION-BASED REPRESENTATIONS -- Piecewise Local Statistics -- Piecewise Discrete Wavelet Transforms -- Polynomial Curve Fitting -- Discrete Fourier Transforms -- 2.2.3 GENERATIVE MODEL-BASED REPRESENTATIONS -- 2.3 SIMILARITY MEASURES -- 2.3.1 SIMILARITY IN TIME -- 2.3.2 SIMILARITY IN SHAPE -- 2.3.3 SIMILARITY IN CHANGE -- 2.4 MINING TASKS -- 2.5 SUMMARY -- 3 - Temporal Data Clustering -- 3.1 INTRODUCTION -- 3.2 OVERVIEW OF CLUSTERING ALGORITHMS -- 3.2.1 PARTITIONAL CLUSTERING -- K-means -- Hidden Markov Model-Based K-Models Clustering -- 3.2.2 HIERARCHICAL CLUSTERING -- Single Linkage -- Complete Linkage -- Average Linkage -- HMM-Based Agglomerative Clustering -- HMM-Based Divisive Clustering -- 3.2.3 DENSITY-BASED CLUSTERING -- Density-Based Spatial Clustering of Applications with Noise -- 3.2.4 MODEL-BASED CLUSTERING -- EM Algorithm -- HMM-Based Hybrid Partitional-Hierarchical Clustering -- HMM-Based Hierarchical Metaclustering -- 3.3 CLUSTERING VALIDATION -- 3.3.1 CLASSIFICATION ACCURACY -- 3.3.2 ADJUSTED RAND INDEX -- 3.3.3 JACCARD INDEX -- 3.3.4 MODIFIED HUBERT'S Γ INDEX -- 3.3.5 DUNN'S VALIDITY INDEX -- 3.3.6 DAVIES-BOULDIN VALIDITY INDEX -- 3.3.7 NORMALIZED MUTUAL INFORMATION -- 3.4 SUMMARY -- 4 - Ensemble Learning -- 4.1 INTRODUCTION -- 4.2 ENSEMBLE LEARNING ALGORITHMS -- Bagging -- Boosting -- 4.3 COMBINING METHODS -- Linear Combiner -- Product Combiner…”

Tabla de Contenidos: “…The AR(1) model ; Regression extensions: AR(1) errors and time-varying parameters ; Autoregressive and moving average processes ; ARMA processes ; Correlograms ; ARMA model identification -- Part III: Modeling financial asset returns. …”

Tabla de Contenidos: “…Polynomial time versus exponential time algorithms -- 2.6. Average, best and worst case complexities -- 2.7. …”

Tabla de Contenidos: “…Performing a normality test with SciPy -- Creating a NumPy masked array -- Disregarding negative and extreme values -- Summary -- Chapter 5: Retrieving, Processing, and Storing Data -- Writing CSV files with NumPy and Pandas -- The binary .npy and pickle formats -- Storing data with PyTables -- Reading and writing Pandas DataFrames to HDF5 stores -- Reading and writing to Excel with Pandas -- Using REST web services and JSON -- Reading and writing JSON with Pandas -- Parsing RSS and Atom feeds -- Parsing HTML with Beautiful Soup -- Summary -- Reference -- Chapter 6: Data Visualization -- The matplotlib subpackages -- Basic matplotlib plots -- Logarithmic plots -- Scatter plots -- Legends and annotations -- Three-dimensional plots -- Plotting in Pandas -- Lag plots -- Autocorrelation plots -- Plot.ly -- Summary -- Chapter 7: Signal Processing and Time Series -- The statsmodels modules -- Moving averages -- Window functions -- Defining cointegration -- Autocorrelation -- Autoregressive models -- ARMA models -- Generating periodic signals -- Fourier analysis -- Spectral analysis -- Filtering -- Summary -- Chapter 8: Working with Databases -- Lightweight access with sqlite3 -- Accessing databases from Pandas -- SQLAlchemy -- Installing and setting up SQLAlchemy -- Populating a database with SQLAlchemy -- Querying the database with SQLAlchemy -- Pony ORM -- Dataset - databases for lazy people -- PyMongo and MongoDB -- Storing data in Redis -- Storing data in memcache -- Apache Cassandra -- Summary -- Chapter 9: Analyzing Textual Data and Social Media -- Installing NLTK -- About NLTK -- Filtering out stopwords, names, and numbers -- The bag-of-words model -- Analyzing word frequencies -- Naive Bayes classification -- Sentiment analysis -- Creating word clouds -- Social network analysis -- Summary -- Chapter 10: Predictive Analytics and Machine Learning…”

Tabla de Contenidos: “…Intro -- Table of Contents -- About the Authors -- About the Technical Reviewer -- Acknowledgments -- Introduction -- Chapter 1: An Introduction to Hibernate 6 -- Plain Old Java Objects (POJOs) -- Building a Project -- Hibernate As a Persistence Solution -- Summary -- Chapter 2: Integrating and Configuring Hibernate -- The Steps Needed to Integrate and Configure Hibernate -- Understanding Where Hibernate Fits into Your Java Application -- Deploying Hibernate -- Installing Maven -- Connection Pooling -- Using JNDI -- Summary -- Chapter 3: Building a Simple Application -- A Simple Application -- Relationships and Cardinality -- A First Attempt -- Writing Data -- Rounding Out the Data Model -- Reading Data -- Updating Data -- Persistence Contexts -- Removing Data -- A Note on Transactions -- The Full Test for Rankings -- Writing Our Sample Application -- Add a Ranking -- Update a Ranking -- Remove a Ranking -- Find Average Ranking for a Subject's Skill -- Find All Rankings for a Subject -- Find the Highest-Ranked Subject for a Skill -- Putting It All Together -- Summary -- Chapter 4: The Persistence LifeCycle -- Introducing the Lifecycle -- Entities, Classes, and Names -- Identifiers -- Entities and Associations -- Saving Entities -- Object Equality and Identity -- Loading Entities -- Merging Entities -- Refreshing Entities -- Updating Entities -- Deleting Entities -- Cascading Operations -- Lazy Loading, Proxies, and Collection Wrappers -- Querying Objects -- Summary -- Chapter 5: An Overview of Mapping -- Why Mapping Cannot Easily Be Automated -- Primary Keys -- Lazy Loading -- Associations -- The One-to-One Association -- The One-to-Many and Many-to-One Associations -- The Many-to-Many Association -- Applying Mappings to Associations -- Other Supported Features -- Specification of (Database) Column Types and Sizes…”

Tabla de Contenidos: “…Chapter 05: Making Informed Decisions -- Factors influencing human decisions -- Human decision-making traps -- Trap #1: Over-confidence bias -- Trap #2: Anchoring bias -- Trap #3: Risk aversion -- Trap #4: Sunk costs -- Trap #5: Framing -- Trap #6: Bandwagon effect -- Trap #7: Confirmation bias -- Trap #8: Decisions based on averages -- Avoiding decision-making traps -- Exploring decision-making strategies -- Informed decision-making framework -- Decision matrix -- Pugh decision matrix -- OODA loop -- Critical thinking in decision making -- Summary -- References -- Chapter 06: Prediction and Statistics -- What is prediction? …”

Tabla de Contenidos: “…The impact of different policy options including functioning elements -- 5.5.1. Using an averaging algorithm…”

Tabla de Contenidos: “…Display Swap Usage in HP-UX; 1.10.8. Show Server Load Averages; 1.10.9. Use iostat; 1.10.10. Automate iostat Collection…”

Tabla de Contenidos: “…-- How to Choose the Right One -- Chapter 17: Tips on Managing Large Accounts -- How to Network Around An Account -- How to Get Extra Work From the Account -- Shaping the Strategy of Their Senior Managers -- When a Team Runs the Account -- Chapter 18: Tips on Negotiation -- Five Questions That Will Prepare Your Negotiation Position -- Nine Rules for the Actual Negotiations -- Group Negotiation -- Common Situations When Negotiating -- How Professional Buyers Buy -- Chapter 19: How to Measure Performance -- Measuring Your Performance Against the Competition -- Measuring Your Own Performance -- Your Real Chances of Winning the Work -- Sales Reporting -- Rewarding Sales Achievement -- Chapter 20: So What Makes the Difference Between Average and Top-Flight Sales Performance? -- Motivation and Goals -- The Seven Ways You Can Create Luck -- Bibliography -- Index -- Would You Like to Know More?…”

Tabla de Contenidos: “…Machine generated contents note: Preface Acknowledgments Chapter 1: Discount Rates and Returns Estimating Returns Geometric and Arithmetic Averages Caveats to Return Extrapolation Discounting Present Values of Cash Flow Streams Internal Rate of Return and Yield to Maturity Real and Nominal Returns Summary Chapter 2: Fixed Income Securities Coupon Bearing Bonds Infinite Cash Flow Streams (Perpetuities) General Pricing Formulas for Finite Cash Flow Streams Interest Rate Risk Analysis of Duration Interest Rate Risk Dynamics Immunization and Duration Applications - Liability Discounting and Cash Matching Pension Logic Risky Coupons Inflation Risk and TIPS A Bond Portfolio Strategy (Optional) Summary Appendix 2.1: Solving Infinite and Finite Power Series References Chapter 3: Term Structure Discounting Using Spot Rates Forward Rates NPV revisited Short Rates The Bootstrap Method Duration Redux Summary Chapter 4: Equity The Determination of Stock Prices Discount Rates Redux Price and Dividend Multiples Extrapolating Multiples to Forecast Returns Pitfalls of Trend Analysis The Gordon Growth Model Sources of Return Summary References Chapter 5: Portfolio Construction Stochastic Returns and Risk Diversification The Efficient Frontier Markowitz Portfolio Selection Criteria Capital Market Line and the CAPM Performance Evaluation Summary Appendix 5.1: Statistical Review Appendix 5.2: Risk Adjusted Performance References Chapter 6: Optimal Portfolios Portfolio 1: Minimum Variance Portfolio (Fully Invested) Portfolio 2: Minimum Variance Portfolios with Targeted Return Portfolio 3: Minimum Variance Portfolios with No Short Sales Portfolio 4: Minimum Variance Portfolios with Capped Allocations Portfolio 5: Maximum Risk-Adjusted Return Performance Attribution The Efficient Frontier (Again) Summary Appendix 6.1: Matrix Operations Chapter 7: Data and Applications Analyzing Returns on a Ten Asset Portfolio Performance Attribution Changing the Investment Horizon Benchmarking to the Market Portfolio The Cost of Constraints A Bond Strategy Summary Chapter 8: Anomalies Deviations from the CAPM Behavioral Finance Summary References Chapter 9: Factor Models Arbitrage Pricing Theory (APT) Factor Selection Model Estimation Principal Components Applications and Examples Summary References Chapter 10: Active Portfolio Management Active Portfolio Construction and Attribution Analysis Performance Attribution Summary Appendix 10.1: Active Space Chapter 11: Risk The Failure of VaR Taxonomy of Risk Visualizing Risk Estimating Volatilities Maximum Likelihood Estimation (Optional) Credit Risk Adjusting for Leverage Adjusting for Illiquidity Other Risks Summary References Chapter 12: Monte Carlo Methods Example 1: Generating Random Numbers - Estimating pi Example 2: Confirming the Central Limit Theorem Example 3: Credit Default Risk Non-Normal Distributions The Gaussian Copula Summary References Chapter 13: Systemic Risk Extreme Value Theory Estimating the Hazards of Downside Risks A Systemic Risk Indicator Summary References Chapter 14: Incorporating Subjective Views Methodological Concepts An Example using Black-Litterman Active Space Risk Attribution Summary References Chapter 15: Futures, Forwards, and Swaps Institutional Detail and Futures Mechanics The Relationship between Spot Prices and Forward (Futures) Prices Hedging Basis Risk Hedging Portfolio Risk Futures Pricing Swaps Summary References Chapter 16: Introduction to Options Option Payoffs and Put-Call Parity Pricing European Call Options Pricing European Put Options Option Strategies Real Options Summary References Chapter 17: Models of Stock Price Dynamics Stock Price Dynamics Ito Processes Lognormal Stock Prices Deriving the Parameters of the Binomial Lattice Black-Scholes-Merton Model The Greek Letters Monte Carlo Methods Summary Appendix 17.1: Derivation of Ito's Lemma Chapter 18: Hedging Portfolio Risk Simple Hedging Strategies S&P 500 Index Puts Selling Volatility VIX Calls Liability Driven Investment Summary References Chapter 19: Private Equity The Private Equity Model Return and Risk Methodology Summary Appendix 19.1: CAPM References Chapter 20: Structured Credit Securitization Credit Enhancement Basics of Pricing Interest Rate Derivatives Interest Rate Dynamics CDO Valuation The Crash of the Housing Bubble Summary References Chapter 21: Optimal Rebalancing Trigger Strategies and No-trade Regions An Optimal Control Problem Implications Optimal Rebalancing in a Static Optimization Model The Comparative Statics of Transactions Costs References Chapter 22: Data Problems* Covariance Estimation An Example Empirical Results Overlapping Observations Conclusions Appendix 22.1: Covariance Matrix Estimation Removing the effects of smoothing References About the Author Index…”

Tabla de Contenidos: “…7.3 Filter Response Characteristics 129 -- 7.4 Specification of Filter Type 131 -- 7.5 Generalized Filter Design Procedure 132 -- 7.6 Design of Active Lowpass Filters 136 -- 7.7 Design of Passive RF Filters 139 -- Problems 146 -- References 148 -- 8 HOW TO DESIGN DIGITAL FILTERS 149 -- 8.1 Review of Sampling 150 -- 8.2 Using the z-Transform to Determine the Transfer Function and Frequency Response of Digital Filters 155 -- 8.3 FIR and IIR Digital Filters 161 -- 8.3.1 FIR Filters 162 -- 8.3.2 IIR Filters 165 -- 8.3.3 Comparisons between FIR and IIR Filters 167 -- 8.4 Design of Simple and Practical Digital Filters 168 -- 8.4.1 Averaging Lowpass FIR Filter 168 -- 8.4.2 Lowpass FIR/IIR Filter 171 -- Problems 177 -- References 181 -- 9 HOW TO WORK WITH RF SIGNALS 183 -- 9.1 Energy Transfer 185 -- 9.2 Signal Reflections 187 -- 9.3 Effect of Signal Reflections on Digital Signals 190 -- 9.4 Effect of Signal Reflections on Narrowband Signals 195 -- 9.5 The Smith Chart 198 -- 9.6 Using the Smith Chart to Display Impedance Versus Frequency 205 -- 9.7 Final Comments Regarding the Smith Chart 205 -- Problems 206 -- References 209 -- 10 GETTING A JOB-KEEPING A JOB-ENJOYING YOUR WORK 211 -- 10.1 Getting a Job 212 -- 10.1.1 Getting an Interview 214 -- 10.1.2 Preparing for an Interview 216 -- 10.1.3 The Interview 217 -- 10.1.4 Selecting the Right Offer 220 -- 10.2 Keeping a Job 221 -- 10.2.1 The First Year 221 -- 10.2.2 After the First Year 224 -- 10.3 Enjoying Your Work 227 -- Afterword 231 -- Answers to Problems 233 -- Index 243.…”

Tabla de Contenidos: “…Substituting One Substring for Another -- Case Study: Generating Account Numbers, Part 2 -- 8 Working with Logical and Information Functions -- Adding Intelligence with Logical Functions -- Case Study: Building an Accounts Receivable Aging Worksheet -- Getting Data with Information Functions -- 9 Working with Lookup Functions -- Understanding Lookup Tables -- The CHOOSE( ) Function -- Looking Up Values in Tables -- 10 Working with Date and Time Functions -- How Excel Deals with Dates and Times -- Using Excel's Date Functions -- Using Excel's Time Functions -- Case Study: Building an Employee Time Sheer -- 11 Working with Math Functions -- Understanding Excel's Rounding Functions -- Case Study: Rounding Billable Time -- Summing Values -- MOD( ) Function -- Generating Random Numbers -- 12 Working with Statistical Functions -- Understanding Descriptive Statistics -- Counting Items with the COUNT( ) Function -- Calculating Averages -- Calculating Extreme Values -- Calculating Measures of Variation -- Working with Frequency Distributions -- Using the Analysis ToolPak Statistical Tools -- III: BUILDING BUSINESS MODELS -- 13 Analyzing Data with Tables -- Converting a Range to a Table -- Basic Table Operations -- Sorting a Table -- Filtering Table Data -- Referencing Tables in Formulas -- Excel's Table Functions -- Case Study: Applying Statistical Table Functions to a Defects Database -- 14 Analyzing Data with PivotTables -- What Are PivotTables? …”

Tabla de Contenidos: “…Machine generated contents note: Foreword ix Preface xi Acknowledgements xv 1 Introduction 1 1.1 Motivation 1 1.2 Basic Fi-Wi System Architecture 10 1.3 Major Issues 12 1.4 Other Fiber Feeder Approaches 13 1.5 Book Outline 14 2 Important Fi-Wi Link Elements 17 2.1 RF-Optical Modulation 17 2.2 The Fiber Channel 29 2.3 Optical Receiver 36 2.4 Brief Review of Baseband-RF Modulation Techniques 40 2.5 The Wireless Channel 42 3 Power Link Budget and Cumulating SNR 49 3.1 Introduction 49 3.2 System Description 50 3.3 Optical Signal to Noise Ratio (OSNR) 51 3.4 Cumulative Signal to Noise Ratio (cSNR) 57 3.5 RAP Design Considerations 58 3.6 Summary 62 4 An Improved Expression for Relative Intensity Noise 63 4.1 Basics 63 4.2 The Fundamental Noise Processes in Radio over Fiber Links 64 4.3 The Signal to Noise Ratio 69 4.4 Numerical Evaluation and Discussion 71 4.5 Summary 72 5 Subcarrier Multiplexed ROF Downlink 75 5.1 Introduction 75 5.2 Background 75 5.3 The ROF Downlink Channel 77 5.4 The Wireless Downlink Channel 91 5.5 Numerical Evaluation and Discussion 92 6 Subcarrier Multiplexed ROF Uplink 97 6.1 The Wireless Uplink Channel 97 6.2 The ROF Uplink Channel 99 6.3 Signals to Distortion, Interference and Noise Ratios 111 6.4 Numerical Evaluations and Discussion 113 6.5 Summary 115 7 Externally Modulated ROF Links 121 7.1 Mach-Zehnder Modulator 121 7.2 Electro-Absorption Modulator (EAM) 125 7.3 Reflective Semiconductor Optical Amplifier (RSOA) 128 7.4 Optimization of the MZI Bias Voltage 128 7.5 Subcarrier Multiplexed Signals in MZI 135 8 DSP Modeling of the ROF Link Nonlinearity 141 8.1 Introduction 141 8.2 Various Attempts to Reduce NLD 142 8.3 DSP Approaches 144 8.4 Basics of DSP for Nonlinear Systems 146 8.5 Baseband Representation of a Passband Complex Nonlinear System 148 8.6 Nonlinear Modeling of Fi-Wi Link 149 9 Adaptive Compensation for the ROF Link Nonlinearity 151 9.1 Adaptive Modeling of the ROF Link 151 9.2 Asymmetric Compensation 159 9.3 Summary 169 10 Joint Estimation of the Fiber Wireless Channel 171 10.1 The Wiener and Hammerstein System Model for Fi-Wi Links 171 10.2 Fiber-Wireless Channel Estimation 172 10.3 Case Study 180 10.4 Summary 182 11 Joint Equalization for the Fiber Wireless Channel 185 11.1 Equalization of the Wireless Channel 185 11.2 Optimization of Polynomial Filter Parameters 189 11.3 Optimization of Linear Filter Parameters 191 11.4 Summary 196 12 Performance Evaluation of the Hammerstein type DFE 197 12.1 Evaluation of the Polynomial Filter 197 12.2 Evaluation of Linear Filters 203 12.3 Case Study 204 12.4 Summary 212 13 Multiuser CDMA Fi-Wi Systems 213 13.1 Multiuser Fi-Wi Uplink Model 213 13.2 Correlation Relationships 215 13.3 ROF Channel Estimation 220 13.4 Case Study 221 13.5 Fiber-Wireless Uplink Equalization 224 13.6 Equalization: Simulation Results and Discussion 225 13.7 Summary 227 14 Fi-Wi for 4G, 5G and OFDM Wireless Networks 229 14.1 Brief History of Cellular Communication Systems 230 14.2 Wireless Access Schemes 232 14.3 Peak to Average Power Ratio Reduction Techniques 235 14.4 OFDM ROF System Improvement 237 14.5 Combinations of OFDMA and CDMA 241 14.6 Summary 242 References 243 References 248 List of Abbreviations 249 …”