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Data-Driven Modeling, Filtering and Control

. In the era of big data, IoT and cyber-physical systems, this subject is of growing importance, as data-driven approaches are key enablers to;

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Predictive Filtering for Microsatellite Control System

filtering, state estimation problem and real-time operation of spacecraft control systems in aerospace engineering. The book gives a systematically;

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Data-Driven Science and Engineering

Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This textbook brings together machine;

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Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis

how a data-driven modeling approach can be utilized to take advantage of the relation between the cyber and the physical domain of the CPS to;

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Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis

how a data-driven modeling approach can be utilized to take advantage of the relation between the cyber and the physical domain of the CPS to;

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Modeling the 3D Conformation of Genomes

of chromosomes in the cell nucleus. Chapters explain how to convert raw experimental data into 3D conformations, and how to use models to better;

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Modeling the 3D Conformation of Genomes

of chromosomes in the cell nucleus. Chapters explain how to convert raw experimental data into 3D conformations, and how to use models to better;

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Adaptive Learning Methods for Nonlinear System Modeling

prediction, network security, vehicular networks, active noise control, information forensics and security, tracking control in mobile robots, power;

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Data-Driven Science and Engineering

Data-driven discovery is revolutionizing how we model, predict, and control complex systems. Now with Python and MATLAB (R), this textbook;

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Kalman Filtering

accelerometers, inertial navigation systems, and freeway traffic control. Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal;

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Nonlinear Stochastic Systems with Incomplete Information

text begins with a focus on H filtering and control problems associated with general classes of nonlinear stochastic discrete-time systems;

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Practical Issues of Intelligent Innovations

of research that varies from applications in industrial data science to those in applied science. Today the word INNOVATION is more and more connected;

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Data-Driven Fault Detection and Reasoning for Industrial Monitoring

control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a;

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Data-Driven Traffic Engineering

Data-Driven Traffic Engineering: Understanding of Traffic and Applications Based on Three-Phase Traffic Theory shifts the current focus;

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Modeling and Control of Batch Processes

Modeling and Control of Batch Processes presents state-of-the-art techniques ranging from mechanistic to data-driven models. These methods;

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Kalman Filtering

topical research data in the study of Kalman filtering, including Kalman filtering in the detection and analysis of voltage dips, short;

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Data-Driven Design of Fault Diagnosis and Fault-Tolerant Control Systems

Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems presents basic statistical process monitoring, fault diagnosis;

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Distributed Cooperative Control and Communication for Multi agent Systems

rigid body systems. The model-based and data-driven control method are employed to design the (optimal) cooperative control protocol. The;

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Distributed Cooperative Control and Communication for Multi agent Systems

rigid body systems. The model-based and data-driven control method are employed to design the (optimal) cooperative control protocol. The;

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Approximate Kalman Filtering

Kalman filtering algorithm gives optimal (linear, unbiased and minimum error-variance) estimates of the unknown state vectors of a linear;

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Data-Driven Reservoir Modeling

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Measurement Data Modeling and Parameter Estimation

Measurement Data Modeling and Parameter Estimation integrates mathematical theory with engineering practice in the field of measurement;

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Measurement Data Modeling and Parameter Estimation

Measurement Data Modeling and Parameter Estimation integrates mathematical theory with engineering practice in the field of measurement;

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Advances in Motion Sensing and Control for Robotic Applications

This book reports on advances in sensing, modeling and control methods for different robotic platforms such as multi-degree of freedom;

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Dynamic Data-Driven Environmental Systems Science

is informed by the environmental context; algorithms for modeling and simulation, downscaling, model reduction, data assimilation, uncertainty;

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Hybrid Self-Organizing Modeling Systems

?cation, or control of complex systems. Modeling is done theory-driven by logical-mathematical methods or data-driven based on observational data;

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Stochastic Control and Filtering over Constrained Communication Networks

Stochastic Control and Filtering over Constrained Communication Networks presents up-to-date research developments and novel methodologies;

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