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  • Reduced-Order Modeling (ROM) for Simulation and Optimization

    Powerful Algorithms as Key Enablers for Scientific Computing

    This edited monograph collects research contributions and addresses the advancement of efficient numerical procedures in the area of model order reduction (MOR) for simulation, optimization and control. The topical scope includes, but is not limited to, new out-of-the-box algorithmic solutions for scientific computing, e.g. reduced basis methods for industrial problems and MOR approaches for ... Read more

    $89.99 USD

  • Mathematical Modeling, Simulation and Optimization for Power Engineering and Management

    Series series Mathematics and Statistics (R0)
    This edited monograph offers a summary of future mathematical methods supporting the recent energy sector transformation. It collects current contributions on innovative methods and algorithms. Advances in mathematical techniques and scientific computing methods are presented centering around economic aspects, technical realization and large-scale networks.Over twenty authors focus on the ... Read more

    $98.99 USD

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    Fundamentals of Least Mean Squares with MATLAB®

    Adaptive filters are used in many diverse applications, appearing in everything from military instruments to cellphones and home appliances. Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB® covers the core concepts of this important field, focusing on a vital part of the statistical signal processing area—the least mean square (LMS) adaptive filter.This largely self-contained ... Read more

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  • Taming Heterogeneity and Complexity of Embedded Control

    This book gathers together a selection of papers presented at the Joint CTS-HYCON Workshop on Nonlinear and Hybrid Control held at the Paris Sorbonne, France, 10-12 July 2006. The main objective of the Workshop was to promote the exchange of ideas and experiences and reinforce scientific contacts in the large multidisciplinary area of the control of nonlinear and hybrid systems. ... Read more

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  • Trends in PDE Constrained Optimization

    Series series Mathematics and Statistics (R0)
    Optimization problems subject to constraints governed by partial differential equations (PDEs) are among the most challenging problems in the context of industrial, economical and medical applications. Almost the entire range of problems in this field of research was studied and further explored as part of the Deutsche Forschungsgemeinschaft (DFG) priority program 1253 on “Optimization with ... Read more

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  • Recent Advances in Model Predictive Control

    Theory, Algorithms, and Applications

    Series series Engineering (R0)
    This book focuses on distributed and economic Model Predictive Control (MPC) with applications in different fields. MPC is one of the most successful advanced control methodologies due to the simplicity of the basic idea (measure the current state, predict and optimize the future behavior of the plant to determine an input signal, and repeat this procedure ad infinitum) and its capability to deal ... Read more

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  • Variable-Structure Approaches

    Analysis, Simulation, Robust Control and Estimation of Uncertain Dynamic Processes

    Edited by Andreas Rauh, Luise Senkel ...
    Series series Engineering (R0)
    This edited book aims at presenting current research activities in the field of robust variable-structure systems. The scope equally comprises highlighting novel methodological aspects as well as presenting the use of variable-structure techniques in industrial applications including their efficient implementation on hardware for real-time control. The target audience primarily comprises research ... Read more

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  • Math for the Digital Factory

    Series series Mathematics and Statistics (R0)
    This volume provides a unique collection of mathematical tools and industrial case studies in digital manufacturing. It addresses various topics, ranging from models of single production technologies, production lines, logistics and workflows to models and optimization strategies for energy consumption in production.The digital factory represents a network of digital models and simulation and 3D ... Read more

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  • Model Reduction of Complex Dynamical Systems

    Series series Mathematics and Statistics (R0)
    This contributed volume presents some of the latest research related to model order reduction of complex dynamical systems with a focus on time-dependent problems. Chapters are written by leading researchers and users of model order reduction techniques and are based on presentations given at the 2019 edition of the workshop series Model Reduction of Complex Dynamical Systems – MODRED, held at the ... Read more

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  • Hands-On Mathematics for Deep Learning

    Build a solid mathematical foundation for training efficient deep neural networks

    by Jay Dawani ...
    A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architecturesKey FeaturesUnderstand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep neural networksLearn the mathematical concepts needed to understand how deep learning models functionUse deep learning for solving problems related to vision, ... Read more

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  • Scientific Computing in Electrical Engineering

    SCEE 2014, Wuppertal, Germany, July 2014

    Series series Springer Nature Proceedings excluding Computer Science
    This book is a collection of selected papers presented at the 10th International Conference on Scientific Computing in Electrical Engineering (SCEE), held in Wuppertal, Germany in 2014. The book is divided into five parts, reflecting the main directions of SCEE 2014: 1. Device Modeling, Electric Circuits and Simulation, 2. Computational Electromagnetics, 3. Coupled Problems, 4. Model Order ... Read more

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  • Advanced Kalman Filtering, Least-Squares and Modeling

    A Practical Handbook

    This book is intended primarily as a handbook for engineers who must design practical systems.Its primary goal is to discuss model development in sufficient detail so that the reader may design an estimator that meets all application requirements and is robust to modeling assumptions. Since it is sometimes difficult to a priori determine the best model structure, use of exploratory data analysis ... Read more

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