Gang Zheng – författare

The key for lasting competitive advantage lies in embracing innovation as a core value and managing it effectively. Innovation Management provides a comprehensive overview of innovation theory and a framework for implementation, intended for business school students of Innovation Management, managers, and practitioners alike. In this new text, authors Jin Chen and Gang Zheng examine innovation from the perspectives of strategy, internal processes, resource management, and organizational culture. Numerous case studies, illustrating both successes and failures in innovation, include Tesla, P&G, Apple, Uber, Google, NVIDIA, Haier Group, Motorola, and Nokia.

Staring from a systematic introduction to the types, process and models of innovation, the authors present a strategical management framework that includes models for indigenous innovation, total innovation, open innovation and holistic innovation. They outline the key roles played by management of capital, information and knowledge systems, human resources, and IP rights. Organizational systems that are designed to stimulate innovation within the corporation are detailed, and finally the authors examine the future of innovation management, focusing the need for sustainable innovation that recognized the importance of environmental and ecological concerns.

Analysis of Genetic Association Studies is both a graduate level textbook in statistical genetics and genetic epidemiology, and a reference book for the analysis of genetic association studies. Students, researchers, and professionals will find the topics introduced in Analysis of Genetic Association Studies particularly relevant.  The book is applicable to the study of statistics, biostatistics, genetics and genetic epidemiology. 

In addition to providing derivations, the book uses real examples and simulations to illustrate step-by-step applications.  Introductory chapters on probability and genetic epidemiology terminology provide the reader with necessary background knowledge.  The organization of this work allows for both casual reference and close study. 

This book presents a differential geometric method for designing nonlinear observers for multiple types of nonlinear systems, including single and multiple outputs, fully and partially observable systems, and regular and singular dynamical systems. It is an exposition of achievements in nonlinear observer normal forms.

The book begins by discussing linear systems, introducing the concept of observability and observer design, and then explains the difficulty of those problems for nonlinear systems. After providing foundational information on the differential geometric method, the text shows how to use the method to address observer design problems. It presents methods for a variety of systems. The authors employ worked examples to illustrate the ideas presented.

Observer Design for Nonlinear Dynamical Systems will be of interest to researchers, graduate students, and industrial professionals working with control of mechanical and dynamical systems.