There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Data Mining Practical Machine Learning Tools and Techniques

This handbook looks to provide academics and students with a comprehensive and holistic understanding of the phenomenon of innovation. Innovation spans a number of fields within the social sciences and humanities: Management, Economics, Geography, Sociology, Politics, Psychology, and History. Consequently, the rapidly increasing body of literature on innovation is characterized by a multitude of perspectives based on, or cutting across, existing disciplines and specializations. Scholars of innovation can come from such diverse starting points that much of this literature can be missed, and so constructive dialogues missed. The editors of The Oxford Handbook of Innovation have carefully selected and designed twenty-one contributions from leading academic experts within their particular field, each focusing on a specific aspect of innovation. These have been organized into four main sections, the first of which looks at the creation of innovations, with particular focus on firms and networks. Section Two provides an account of the wider systematic setting influencing innovation and the role of institutions and organizations in this context. Section Three explores some of the diversity in the working of innovation over time and across different sectors of the economy, and Section Four focuses on the consequences of innovation with respect to economic growth, international competitiveness, and employment. An introductory overview, concluding remarks, and guide to further reading for each chapter, make this handbook a key introduction and vital reference work for researchers, academics, and advanced students of innovation. Contributors to this volume - Jan Fagerberg, University of Oslo William Lazonick, INSEAD Walter W. Powell, Stanford University Keith Pavitt, SPRU Alice Lam, Brunel University Keith Smith, INTECH Charles Edquist, Linkoping David Mowery, University of California, Berkeley Mary O'Sullivan, INSEAD Ove Granstrand, Chalmers Bjorn Asheim, University of Lund Rajneesh Narula, Copenhagen Business School Antonello Zanfei, Urbino Kristine Bruland, University of Oslo Franco Malerba, University of Bocconi Nick Von Tunzelmann, SPRU Ian Miles, University of Manchester Bronwyn Hall, University of California, Berkeley Bart Verspagen , ECIS Francisco Louca, ISEG Manuel M. Godinho, ISEG Richard R. Nelson, Mario Pianta, Urbino Bengt-Ake Lundvall, Aalborg

The Oxford Handbook of Innovation

Praise for the Third Edition: "This is one of the best books available. Its excellent organizational structure allows quick reference to specific models and its clear presentation . . . solidifies the understanding of the concepts being presented."IIE Transactions on Operations EngineeringThoroughly revised and expanded to reflect the latest developments in the field, Fundamentals of Queueing Theory, Fourth Edition continues to present the basic statistical principles that are necessary to analyze the probabilistic nature of queues. Rather than presenting a narrow focus on the subject, this update illustrates the wide-reaching, fundamental concepts in queueing theory and its applications to diverse areas such as computer science, engineering, business, and operations research.This update takes a numerical approach to understanding and making probable estimations relating to queues, with a comprehensive outline of simple and more advanced queueing models. Newly featured topics of the Fourth Edition include:Retrial queuesApproximations for queueing networksNumerical inversion of transformsDetermining the appropriate number of servers to balance quality and cost of serviceEach chapter provides a self-contained presentation of key concepts and formulae, allowing readers to work with each section independently, while a summary table at the end of the book outlines the types of queues that have been discussed and their results. In addition, two new appendices have been added, discussing transforms and generating functions as well as the fundamentals of differential and difference equations. New examples are now included along with problems that incorporate QtsPlus software, which is freely available via the book's related Web site.With its accessible style and wealth of real-world examples, Fundamentals of Queueing Theory, Fourth Edition is an ideal book for courses on queueing theory at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners who analyze congestion in the fields of telecommunications, transportation, aviation, and management science.

Fundamentals of Queueing Theory

This chapter is concerned with the stochastic stability for a class of S-MJS with time-variant delays. By the Lyapunov function approach, together with a piecewise analysis method, sufficient conditions are proposed to guarantee the stochastic stability of the S-MJS. As more time-delay information is used, our results are much less conservative than some existing ones in literature. Finally, two examples are given to show the effectiveness and advantages of the proposed techniques.

Stochastic Stability of Semi-Markovian Jump Systems

Robust sampled‐data model predictive control for networked systems with time‐varying delay

In this paper, the problem of containment control is investigated for a class of multi-agent systems with second-order integrator dynamics. A directed graph is considered, and a pair of matrix norm and vector norm is designed. Accounting for the limitation of the finite bandwidth channels, quantized communication topology based on the encoding–decoding strategy is designed, in which the quantizers only have finite quantization levels and it is independent of the initial state of agents. Moreover, the quantizer and controller are jointly designed only using the estimated value of the neighbors’ state information to ensure the system stability with less communication resource. The relationship between the quantization levels and sampling interval is established to guarantee that all the quantizers are not saturated, and thus ensure the asymptotic stability of the system. And a vector norm induced by a constructed matrix norm is applied to reduce the lower boundary of the communication data rate which is free from the dimension and number of agents. Finally, simulation examples are given to show the effectiveness of the new designed techniques.

Containment Control of Multi-agent Systems with Uniform Quantization

This paper addresses the fault estimation problem for discrete-time dynamic systems. First, using a specific system decomposition, we propose a new reduced-order fault estimation observer (RFEO) with multiconstrained idea. A detailed discussion of the RFEO is given. Then, with the help of the slack-variable technique, fault estimation performances are further enhanced to reduce the conservatism generated by the direct design method. Simulation results of a discrete-time aircraft application are presented to illustrate our contributions.

Reduced-order fault estimation observer design for discrete-time systems

The state estimation problem is discussed for discrete Markovian jump
neural networks with time-varying delays in terms of linear matrix inequality
(LMI) approach. The considered transition probabilities are assumed to
be time-variant and partially unknown. The aim of the state estimation
problem is to design a state estimator to estimate the neuron states and
ensure the stochastic stability of the error-state system. A delay-dependent
sufficient condition for the existence of the desired state estimator is proposed.
An explicit expression of the desired estimator is also given. A numerical
example is introduced to show the effectiveness of the given result.

Peng Shi

Papers

Stochastic Stability of Semi-Markovian Jump Systems

Robust sampled‐data model predictive control for networked systems with time‐varying delay

Containment Control of Multi-agent Systems with Uniform Quantization

Reduced-order fault estimation observer design for discrete-time systems

Delay-dependent state estimation for discrete Markovian jump neural networks with time-varying delay