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This revised textbook motivates and illustrates the techniques of applied probability by applications in electrical engineering and computer science (EECS). The author presents information processing and communication systems that use algorithms based on probabilistic models and techniques, including web searches, digital links, speech recognition, GPS, route planning, recommendation systems, classification, and estimation. He then explains how these applications work and, along the way, provides the readers with the understanding of the key concepts and methods of applied probability. Python labs enable the readers to experiment and consolidate their understanding. The book includes homework, solutions, and Jupyter notebooks. This edition includes new topics such as Boosting, Multi-armed bandits, statistical tests, social networks, queuing networks, and neural networks. For ancillaries related to this book, including examples of Python demos and also Python labs used in Berkeley, please email Mary James at mary.james@springer.com. This is an open access book.

Maths for computer scientists --- Communications engineering / telecommunications --- Maths for engineers --- Probability & statistics --- Probability and Statistics in Computer Science --- Communications Engineering, Networks --- Mathematical and Computational Engineering --- Probability Theory and Stochastic Processes --- Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences --- Mathematical and Computational Engineering Applications --- Probability Theory --- Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences --- Applied probability --- Hypothesis testing --- Detection theory --- Expectation maximization --- Stochastic dynamic programming --- Machine learning --- Stochastic gradient descent --- Deep neural networks --- Matrix completion --- Linear and polynomial regression --- Open Access --- Mathematical & statistical software --- Stochastics

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Flood/drought, risk management, and policy: decision-making under uncertainty. Hydrometeorological extremes and their impact on human–environment systems. Regional and nonstationary frequency analysis of extreme events. Detection and prediction of hydrometeorological extremes with observational and model-based approaches. Vulnerability and impact assessment for adaptation to climate change.

spatial downscaling --- MODIS chlorophyll-a --- sentinel-2A MSI --- multiple polynomial regression --- genetic programming --- rainfall variability --- Indian Ocean Dipole (IOD) --- El Niño–Southern Oscillation (ENSO) --- intentional statistical simulation --- satellite-based precipitation --- hydrological modeling --- error propagation --- monsoon-climate watershed --- typhoon-induced rainfall --- prediction --- statistical model --- fuzzy C-means clustering --- China --- remote sensing --- integrated drought monitoring --- meteorological drought --- hydrological drought --- agricultural drought --- Bayesian principal component analysis (BPCA) --- statistical simulation --- extreme precipitation index --- PERSIANN-CDR --- KGE --- linear trend --- Huai River Basin --- Indian Ocean Dipole mode --- El Niño–Southern Oscillation --- singular spectrum analysis --- mutual information --- non-stationarity of seasonal precipitation

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Numerical methods are a specific form of mathematics that involve creating and use of algorithms to map out the mathematical core of a practical problem. Numerical methods naturally find application in all fields of engineering, physical sciences, life sciences, social sciences, medicine, business, and even arts. The common uses of numerical methods include approximation, simulation, and estimation, and there is almost no scientific field in which numerical methods do not find a use. Results communicated here include topics ranging from statistics (Detecting Extreme Values with Order Statistics in Samples from Continuous Distributions) and Statistical software packages (dCATCH—A Numerical Package for d-Variate near G-Optimal Tchakaloff Regression via Fast NNLS) to new approaches for numerical solutions (Exact Solutions to the Maxmin Problem max‖Ax‖ Subject to ‖Bx‖≤1; On q-Quasi-Newton’s Method for Unconstrained Multiobjective Optimization Problems; Convergence Analysis and Complex Geometry of an Efficient Derivative-Free Iterative Method; On Derivative Free Multiple-Root Finders with Optimal Fourth Order Convergence; Finite Integration Method with Shifted Chebyshev Polynomials for Solving Time-Fractional Burgers’ Equations) to the use of wavelets (Orhonormal Wavelet Bases on The 3D Ball Via Volume Preserving Map from the Regular Octahedron) and methods for visualization (A Simple Method for Network Visualization).

Research & information: general --- Mathematics & science --- Clenshaw–Curtis–Filon --- high oscillation --- singular integral equations --- boundary singularities --- local convergence --- nonlinear equations --- Banach space --- Fréchet-derivative --- finite integration method --- shifted Chebyshev polynomial --- Caputo fractional derivative --- Burgers’ equation --- coupled Burgers’ equation --- maxmin --- supporting vector --- matrix norm --- TMS coil --- optimal geolocation --- probability computing --- Monte Carlo simulation --- order statistics --- extreme values --- outliers --- multiobjective programming --- methods of quasi-Newton type --- Pareto optimality --- q-calculus --- rate of convergence --- wavelets on 3D ball --- uniform 3D grid --- volume preserving map --- Network --- graph drawing --- planar visualizations --- multiple root solvers --- composite method --- weight-function --- derivative-free method --- optimal convergence --- multivariate polynomial regression designs --- G-optimality --- D-optimality --- multiplicative algorithms --- G-efficiency --- Caratheodory-Tchakaloff discrete measure compression --- Non-Negative Least Squares --- accelerated Lawson-Hanson solver --- Clenshaw–Curtis–Filon --- high oscillation --- singular integral equations --- boundary singularities --- local convergence --- nonlinear equations --- Banach space --- Fréchet-derivative --- finite integration method --- shifted Chebyshev polynomial --- Caputo fractional derivative --- Burgers’ equation --- coupled Burgers’ equation --- maxmin --- supporting vector --- matrix norm --- TMS coil --- optimal geolocation --- probability computing --- Monte Carlo simulation --- order statistics --- extreme values --- outliers --- multiobjective programming --- methods of quasi-Newton type --- Pareto optimality --- q-calculus --- rate of convergence --- wavelets on 3D ball --- uniform 3D grid --- volume preserving map --- Network --- graph drawing --- planar visualizations --- multiple root solvers --- composite method --- weight-function --- derivative-free method --- optimal convergence --- multivariate polynomial regression designs --- G-optimality --- D-optimality --- multiplicative algorithms --- G-efficiency --- Caratheodory-Tchakaloff discrete measure compression --- Non-Negative Least Squares --- accelerated Lawson-Hanson solver

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Numerical methods are a specific form of mathematics that involve creating and use of algorithms to map out the mathematical core of a practical problem. Numerical methods naturally find application in all fields of engineering, physical sciences, life sciences, social sciences, medicine, business, and even arts. The common uses of numerical methods include approximation, simulation, and estimation, and there is almost no scientific field in which numerical methods do not find a use. Results communicated here include topics ranging from statistics (Detecting Extreme Values with Order Statistics in Samples from Continuous Distributions) and Statistical software packages (dCATCH—A Numerical Package for d-Variate near G-Optimal Tchakaloff Regression via Fast NNLS) to new approaches for numerical solutions (Exact Solutions to the Maxmin Problem max‖Ax‖ Subject to ‖Bx‖≤1; On q-Quasi-Newton’s Method for Unconstrained Multiobjective Optimization Problems; Convergence Analysis and Complex Geometry of an Efficient Derivative-Free Iterative Method; On Derivative Free Multiple-Root Finders with Optimal Fourth Order Convergence; Finite Integration Method with Shifted Chebyshev Polynomials for Solving Time-Fractional Burgers’ Equations) to the use of wavelets (Orhonormal Wavelet Bases on The 3D Ball Via Volume Preserving Map from the Regular Octahedron) and methods for visualization (A Simple Method for Network Visualization).

Clenshaw–Curtis–Filon --- high oscillation --- singular integral equations --- boundary singularities --- local convergence --- nonlinear equations --- Banach space --- Fréchet-derivative --- finite integration method --- shifted Chebyshev polynomial --- Caputo fractional derivative --- Burgers’ equation --- coupled Burgers’ equation --- maxmin --- supporting vector --- matrix norm --- TMS coil --- optimal geolocation --- probability computing --- Monte Carlo simulation --- order statistics --- extreme values --- outliers --- multiobjective programming --- methods of quasi-Newton type --- Pareto optimality --- q-calculus --- rate of convergence --- wavelets on 3D ball --- uniform 3D grid --- volume preserving map --- Network --- graph drawing --- planar visualizations --- multiple root solvers --- composite method --- weight-function --- derivative-free method --- optimal convergence --- multivariate polynomial regression designs --- G-optimality --- D-optimality --- multiplicative algorithms --- G-efficiency --- Caratheodory-Tchakaloff discrete measure compression --- Non-Negative Least Squares --- accelerated Lawson-Hanson solver

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This reprint presents various aspects of the future grid, which is the next generation of the electrical grid and will enable the smart integration of conventional, renewable, and distributed power generation, energy storage, transmission and distribution, and demand management. Renewable energy is crucial in transitioning to a less carbon-intensive economy and a more sustainable energy system. The high penetration and uncertain power outputs of renewable energy pose great challenges to the stable operation of energy systems. The deployment of the smart grid is revolutionary, and also imperative around the world. It involves and deals with multidisciplinary fields such as energy sources, control systems, communications, computational generation, transmission, distribution, customer operations, markets, and service providers. Smart grids are emerging in both developed and developing countries, with the aim of achieving a reliable and secure electricity supply. Smart grids will eventually require standards, policy, and a regulatory framework for successful implementation. This reprint addresses the emerging and advanced green energy technologies for a sustainable and resilient future grid, and provides a platform to enhance interdisciplinary research and share the most recent ideas.

Technology: general issues --- History of engineering & technology --- islanded mode --- microgrid --- decentralized control --- robust tracking --- invariant set --- thermal energy storage --- parabolic dish --- latent heat --- phase change material --- heat transfer fluid --- bio-inspired algorithms --- wireless sensor network --- genetic algorithm --- particle swarm optimization --- advanced metering infrastructure --- blockchain --- Ethereum --- isolated DC–DC converter --- photovoltaics --- LLC resonant converter --- dual-bridge --- wide voltage range --- power optimizer --- coordinated control --- vehicle-to-grid --- primary frequency control --- secondary frequency control --- state of charge --- decentralized --- Simulink model --- dimensionality reduction --- simple linear regression --- multiple linear regression --- polynomial regression --- load forecasting --- VSC (voltage source converter) --- PLL (Phase-Locked Loop) --- weak grid --- small signal stability --- eigenvalues --- demand-side management --- low-power consumer electronic appliances --- low-voltage distribution system --- non-intrusive identification of appliance usage patterns --- power quality --- smart home --- true power factor --- total harmonic distortion --- renewable energy sources --- energy management system --- communication technologies --- microgrid standards --- third-order sliding mode control --- asynchronous generators --- variable speed dual-rotor wind turbine --- direct field-oriented control --- integral-proportional --- transformer --- internal fault currents --- magnetic inrush currents --- extended Kalman filter (EKF) algorithm --- harmonic estimation --- DC microgrid --- fault --- cluster --- DC/DC converter --- fault current limiter (FCL) --- multi-objective --- renewable energy --- profit-based scheduling --- Equilibrium Optimizer --- smart grid --- campus microgrid --- batteries --- prosumer market --- distributed generation --- renewable energy resources --- energy storage system --- distributed energy resources --- demand response --- load clustering techniques --- sizing methodologies --- digital signal processing --- green buildings --- spectral analysis --- spectral kurtosis --- life-cycle cost --- optimal scheduling --- reinforcement learning --- enabling technologies --- energy community --- smart meter --- nanogrid --- platform --- power cloud --- n/a --- isolated DC-DC converter