Presents a scientific history of noise, defining it as an unaesthetic signal which occurs at every level of the universe and which has made significant impact on each period of time, from the Ice Age to the Information Age.
William Gibson meets Tom Clancy in this brilliant and chilling cyberthriller set in the multimedia world of the near furture--where oil is running out, wars are smart, and intelkligent software agents may be the only friends you can trust. In the year 2030--when the world has doubled in population and no one escape the prying eyes of the State--John Grant wants to save the Earth from its addiction to oil and get rich in the process. But the revoultionary new molecule he has patented--an astonishing advance that can split water and produce a virtually limitless supply of cheap feul hydrogen--has marke him as a traitor to his country. . .and as a target. Sufi mystic, genius mathematician and master terroist Hamid Tabriz wants Grant's patent and his mind. Now both goals are within Tabriz's reach, thankls to a chip he has perfected which enables him to place his own mind in another's head. An increasingly chatic world is racing toward annihilation. And John Grant will have to defend it--and himself--from a disembdied place far beyond the confines of space and time: in NANOTIME.
Presents a scientific history of noise, defining it as an unaesthetic signal which occurs at every level of the universe and which has made significant impact on each period of time, from the Ice Age to the Information Age.
Many problems in decision making, monitoring, fault detection, and control require the knowledge of state variables and time-varying parameters that are not directly measured by sensors. In such situations, observers, or estimators, can be employed that use the measured input and output signals along with a dynamic model of the system in order to estimate the unknown states or parameters. An essential requirement in designing an observer is to guarantee the convergence of the estimates to the true values or at least to a small neighborhood around the true values. However, for nonlinear, large-scale, or time-varying systems, the design and tuning of an observer is generally complicated and involves large computational costs. This book provides a range of methods and tools to design observers for nonlinear systems represented by a special type of a dynamic nonlinear model -- the Takagi--Sugeno (TS) fuzzy model. The TS model is a convex combination of affine linear models, which facilitates its stability analysis and observer design by using effective algorithms based on Lyapunov functions and linear matrix inequalities. Takagi--Sugeno models are known to be universal approximators and, in addition, a broad class of nonlinear systems can be exactly represented as a TS system. Three particular structures of large-scale TS models are considered: cascaded systems, distributed systems, and systems affected by unknown disturbances. The reader will find in-depth theoretic analysis accompanied by illustrative examples and simulations of real-world systems. Stability analysis of TS fuzzy systems is addressed in detail. The intended audience are graduate students and researchers both from academia and industry. For newcomers to the field, the book provides a concise introduction dynamic TS fuzzy models along with two methods to construct TS models for a given nonlinear system
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