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Intuitive Understanding of Kalman Filtering with MATLAB (R) (Paperback)
Loot Price: R1,793
Discovery Miles 17 930
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Intuitive Understanding of Kalman Filtering with MATLAB (R) (Paperback)
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The emergence of affordable micro sensors, such as MEMS Inertial
Measurement Systems, are applied in embedded systems and
Internet-of-Things devices. This has brought techniques such as
Kalman Filtering, which are capable of combining information from
multiple sensors or sources, to the interest of students and
hobbyists. This book will explore the necessary background
concepts, helping a much wider audience of readers develop an
understanding and intuition that will enable them to follow the
explanation for the Kalman Filtering algorithm. Key Features:
Provides intuitive understanding of Kalman Filtering approach
Succinct overview of concepts to enhance accessibility and appeal
to a wide audience Interactive learning techniques with code
examples Malek Adjouadi, PhD, is Ware Professor with the Department
of Electrical and Computer Engineering at Florida International
University, Miami. He received his PhD from the Electrical
Engineering Department at the University of Florida, Gainesville.
He is the Founding Director of the Center for Advanced Technology
and Education funded by the National Science Foundation. His
earlier work on computer vision to help persons with blindness led
to his testimony to the U.S. Senate on the committee of Veterans
Affairs on the subject of technology to help persons with
disabilities. His research interests are in imaging, signal
processing and machine learning, with applications in brain
research and assistive technology. Armando Barreto, PhD, is
Professor of the Electrical and Computer Engineering Department at
Florida International University, Miami, as well as the Director of
FIU's Digital Signal Processing Laboratory, with more than 25 years
of experience teaching DSP to undergraduate and graduate students.
He earned his PhD in electrical engineering from the University of
Florida, Gainesville. His work has focused on applying DSP
techniques to the facilitation of human-computer interactions,
particularly for the benefit of individuals with disabilities. He
has developed human-computer interfaces based on the processing of
signals and has developed a system that adds spatialized sounds to
the icons in a computer interface to facilitate access by
individuals with "low vision." With his research team, he has
explored the use of Magnetic, Angular-Rate and Gravity (MARG)
sensor modules and Inertial Measurement Units (IMUs) for
human-computer interaction applications. He is a senior member of
the Institute of Electrical and Electronics Engineers (IEEE) and
the Association for Computing Machinery (ACM). Francisco R. Ortega,
PhD, is an Assistant Professor at Colorado State University and
Director of the Natural User Interaction Lab (NUILAB). Dr. Ortega
earned his PhD in Computer Science (CS) in the field of
Human-Computer Interaction (HCI) and 3D User Interfaces (3DUI) from
Florida International University (FIU). He also held a position of
Post-Doc and Visiting Assistant Professor at FIU. His main research
area focuses on improving user interaction in 3DUI by (a) eliciting
(hand and full-body) gesture and multimodal interactions, (b)
developing techniques for multimodal interaction, and (c)
developing interactive multimodal recognition systems. His
secondary research aims to discover how to increase interest for CS
in non-CS entry-level college students via virtual and augmented
reality games. His research has resulted in multiple peer-reviewed
publications in venues such as ACM ISS, ACM SUI, and IEEE 3DUI,
among others. He is the first-author of the CRC Press book
Interaction Design for 3D User Interfaces: The World of Modern
Input Devices for Research, Applications and Game Development.
Nonnarit O-larnnithipong, PhD, is an Instructor at Florida
International University. Dr. O-larnnithipong earned his PhD in
Electrical Engineering, majoring in Digital Signal Processing from
Florida International University (FIU). He also held a position of
Post-Doctoral Associate at FIU in 2019. His research has focused on
(1) implementing the sensor fusion algorithm to improve orientation
measurement using MEMS inertial and magnetic sensors and (2)
developing a 3D hand motion tracking system using Inertial
Measurement Units (IMUs) and infrared cameras. His research has
resulted in multiple peer-reviewed publications in venues such as
HCI-International and IEEE Sensors.
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