front cover of Developments in Control Theory Towards Glocal Control
Developments in Control Theory Towards Glocal Control
Li Qiu
The Institution of Engineering and Technology, 2012
Glocal control, a term coined by Professor Shinji Hara at The University of Tokyo, represents a new framework for studying behaviour of complex dynamical systems from a feedback control perspective. A large number of dynamical components can be interconnected and interact with each other to form an integrated system with certain functionalities. Such complex systems are found in nature and have been created by man, including gene regulatory networks, neuronal circuits for memory, decision making, and motor control, bird flocking, global climate dynamics, central processing units for computers, electrical power grids, the World Wide Web, and financial markets. A common feature of these systems is that a global property or function emerges as a result of local, distributed, dynamical interactions of components. The objective of 'glocal' (global + local) control is to understand the mechanisms underlying this feature, analyze existing complex systems, and to design and create innovative systems with new functionalities. This book is dedicated to Professor Shinji Hara on the occasion of his 60th birthday, collecting the latest results by leading experts in control theories to lay a solid foundation towards the establishment of glocal control theory in the coming decades.
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front cover of Handbook of Speckle Filtering and Tracking in Cardiovascular Ultrasound Imaging and Video
Handbook of Speckle Filtering and Tracking in Cardiovascular Ultrasound Imaging and Video
Christos P. Loizou
The Institution of Engineering and Technology, 2018
Ultrasound imaging technology has experienced a dramatic change in the last 30 years. Because of its non-invasive nature and continuing improvements in image quality, ultrasound imaging is progressively achieving an important role in the assessment and characterization of cardiovascular imaging. Speckle is inherent in ultrasound imaging giving rise to a granular appearance instead of homogeneous, flat shades of gray, as is visible and as such, speckle can severely compromise interpretation of ultrasound images, particularly in discrimination of small structures. On the other hand, speckle can be used in the detection of time varying phenomena, or tracking tissue motion. The objective of this book is to provide a reference edited volume covering the whole spectrum of speckle phenomena, theoretical background and modelling, algorithms and selected applications in cardiovascular ultrasound imaging and video processing and analysis. The book is organized under the following four parts, Part I: Introduction to Speckle Noise; Part II: Speckle Filtering; Part III: Speckle Tracking; Part IV: Selected Applications in Cardiovascular Imaging.
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front cover of Image Processing for Engineers
Image Processing for Engineers
Andrew E. Yagle and Fawwaz T. Ulaby
Michigan Publishing Services, 2018
[from the Preface] Designed for a course on image processing (IP) aimed at both graduate students as well as undergraduates in their senior year, in any field of engineering, this book starts with an overview in Chapter 1 of how imaging sensors—from cameras to radars to MRIs and CAT—form images, and then proceeds to cover a wide array of image processing topics. The IP topics include: image interpolation, magnification, thumbnails, and sharpening, edge detection, noise filtering, de-blurring of blurred images, supervised and unsupervised learning, and image segmentation, among many others. As a prelude to the chapters focused on image processing (Chapters 3–12), the book offers in Chapter 2 a review of 1-D signals and systems, borrowed from our 2018 book Signals and Systems: Theory and Applications, by Ulaby and Yagle.
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front cover of Medical Imaging Informatics
Medical Imaging Informatics
Machine learning, deep learning and big data analytics
Mamoon Rashid
The Institution of Engineering and Technology, 2024
Medical imaging informatics play an important role in the effectiveness of present-day healthcare systems. Advancement of artificial intelligence, big data analytics, and internet of things technologies contribute greatly to various healthcare applications. Artificial intelligence techniques are contributing to improvements with traditionally human-based systems and ensuring that the accuracy of prediction and diagnosis is being continually enhanced. The development of reliable and accurate healthcare models is becoming ever more possible with the help of machine learning and deep learning technologies. Artificial intelligence has the power to solve many complex problems in medical imaging and is a technology that will help to design the future of many healthcare systems.
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