Learn IT - Books tags sampling

Mathematical Modelling, Optimization, Analytic and Numerical Solutions (Industrial and Applied Mathematics)

Springer, 2020

This book discusses a variety of topics related to industrial and applied mathematics, focusing on wavelet theory, sampling theorems, inverse problems and their applications, partial differential equations as a model of real-world problems, computational linguistics, mathematical models and methods for meteorology, earth systems,...

Digital Signal Processing

McGraw-Hill, 2005

An up-to-the-minute textbook for junior/senior level signal processing courses and senior/graduate level digital filter design courses, this text is supported by a DSP software package known as D-Filter which would enable students to interactively learn the fundamentals of DSP and digital-filter design. The book includes a free license to...

Digital Signal Processing with Examples in MATLAB® (Electrical Engineering & Applied Signal Processing Series)

CRC Press, 2011

Based on fundamental principles from mathematics, linear systems, and signal analysis, digital signal processing (DSP) algorithms are useful for extracting information from signals collected all around us. Combined with today’s powerful computing capabilities, they can be used in a wide range of application areas, including...

Process Control Systems: Application, Design, and Adjustment

McGraw-Hill, 1988

The complete updated edition of this best-selling reference provides an unsurpassed account of process control--from the very basics of theory to advanced control applications. This edition of this guide fully explains control technology principles applied to industrial fluid processes, including time-domain and relative-gain analysis. Control...

Numerical Simulation of Optical Wave Propagation With Examples in MATLAB (SPIE Press Monograph Vol. PM199)

SPIE Press, 2010

Wave-optics simulation is an immensely useful tool for many applications. The simulation techniques in this book are directly applicable to atmospheric imaging, astronomy, adaptive optics, free-space optical communications, and LADAR. In addition, many of the basic techniques are applicable to integrated optics and nonlinear, anisotropic,...

Mathematical Statistics with Resampling and R

John Wiley & Sons, 2011

This book bridges the latest software applications with the benefits of modern resampling techniques

Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. This groundbreaking book shows how to apply modern resampling techniques...

Simulation-Based Algorithms for Markov Decision Processes (Communications and Control Engineering)

Springer, 2013

Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences. Many real-world problems modeled by MDPs have huge state and/or action spaces, giving an opening to the curse of dimensionality and so making practical...

Analysis of Correlated Data with SAS and R

CRC Press, 2007

Previously known as Statistical Methods for Health Sciences, this bestselling resource is one of the first books to discuss the methodologies used for the analysis of clustered and correlated data. While the fundamental objectives of its predecessors remain the same, Analysis of Correlated Data with SAS and R, Third Edition incorporates...

Pregnant in the Time of Ebola: Women and Their Children in the 2013-2015 West African Epidemic (Global Maternal and Child Health)

Springer, 2019

This comprehensive account of the deadliest Ebola outbreak in history examines its devastating effects on West Africa’s most vulnerable populations: pregnant women and children. Noted experts across disciplines assess health care systems’ responses to the epidemic in Liberia, Guinea, and Sierra Leone, emphasizing key...

Hands-On Ensemble Learning with R: A beginner's guide to combining the power of machine learning algorithms using ensemble techniques

Packt Publishing, 2018

Explore powerful R packages to create predictive models using ensemble methods

Key Features

Implement machine learning algorithms to build ensemble-efficient models

Explore powerful R packages to create predictive models using ensemble methods

Learn to...

Forest Analytics with R: An Introduction (Use R!)

Springer, 2010

R is an open-source and free software environment for statistical computing and graphics. R compiles and runs on a wide variety of UNIX platforms (e.g., GNU/Linux and FreeBSD), Windows, and Mac OSX. Since the late 1990s, R has been developed by hundreds of contributors and new capabilities are added each month....

Surrogate Model-Based Engineering Design and Optimization (Springer Tracts in Mechanical Engineering)

Springer, 2019

This book covers some of the most popular methods in design space sampling, ensembling surrogate models, multi-fidelity surrogate model construction, surrogate model selection and validation, surrogate-based robust design optimization, and surrogate-based evolutionary optimization.

Surrogate or metamodels are now...

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