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Due to its abilities to compensate disturbances and uncertainties, disturbance observer based control (DOBC) is regarded as one of the most promising approaches for disturbance-attenuation. One of the first books on DOBC, Disturbance Observer Based Control: Methods and Applications presents novel theory results as well as best practices for applications in motion and process control that have already benefited numerous organizations.
Supplying authoritative guidance in the areas of disturbance estimation and compensation for practical...

This book proposes a theoretical framework identifying external and internal factors that influence internationalization strategy of Chinese brands and brand performance. It explores several key strategies e.g. standardization versus adaptation, price leadership versus branding, OBM export versus OEM export, and incremental versus leap-forward internationalization model. The relationships are examined between various international marketing mix e.g. distribution channel and pricing strategies, and brand performance. Through case studies the text also analyses the internationalization of...

This book covers several major functional carbohydrates widely used in food and other applications. It presents technical details of bio-manufacture, providing direct assistance to researchers and engineers who are interested in applying and producing these carbohydrates. The book first addresses the history and recent developments of a selected number of important functional carbohydrates and then goes on to introduce the source, properties and applications of functional acids, saccharides and certain saccharide derivatives.

This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve key metrics—such as energy-efficiency, throughput, and latency—without sacrificing...