This book is about global navigation satellite systems (GNSS), their two main instru- ments, which are a receiver and a simulator, and their applications. The book is based on an operational off-the-shelf real-time software GNSS receiver and off-the-shelf GNSS signalsimulator.Theacademicversionsofthesetoolsarebundledwiththisbookandfree for readers to use for study and research.
標(biāo)簽： Navigation Geophysics Satellite Digital and
上傳時(shí)間： 2020-06-09
上傳用戶：shancjb
The purpose of this book is to help anyone involved in small-scale geophys- ical surveys. It is not a textbook in the traditional sense, in that it is designed for use in the field and concerns itself with practical matters – with the- ory taking second place. Where theory determines field practice, it is stated, not developed or justified. For example, no attempt is made to explain why four-electrode resistivity works where two-electrode surveys do not.
標(biāo)簽： Field_Geophysics
上傳時(shí)間： 2020-06-09
上傳用戶：shancjb
The purpose of this book is to present detailed fundamental information on a global positioning system (GPS) receiver. Although GPS receivers are popu- larly used in every-day life, their operation principles cannot be easily found in one book. Most other types of receivers process the input signals to obtain the necessary information easily, such as in amplitude modulation (AM) and frequency modulation (FM) radios. In a GPS receiver the signal is processed to obtain the required information, which in turn is used to calculate the user position. Therefore, at least two areas of discipline, receiver technology and navigation scheme, are employed in a GPS receiver. This book covers both areas.
標(biāo)簽： Fundamentals_of_Global_Positionin g_System_Receivers
上傳時(shí)間： 2020-06-09
上傳用戶：shancjb
This book is intended for researchers, teachers, and students willing to ex- plore conceptual bridges between the fields of Automatic Control and Power Electronics. The need to bring the two disciplines closer has been felt, for many years, both by Power Electronics specialists and by Automatic Control theorists, as a means of fruitful interaction between the two scientific com- munities.
標(biāo)簽： Techniques Control Design
上傳時(shí)間： 2020-06-10
上傳用戶：shancjb
The chief objective of Electric Machinery continues to be to build a strong foundation in the basic principles of electromechanics and electric machinery. Through all of its editions, the emphasis of Electric Machinery has been on both physical insight and analytical techniques. Mastery of the material covered will provide both the basis for understanding many real-world electric-machinery applications as well as the foundation for proceeding on to more advanced courses in electric machinery design and control.
標(biāo)簽： Machinery Electric 6th ed
上傳時(shí)間： 2020-06-10
上傳用戶：shancjb
There exist two essentially different approaches to the study of dynamical systems, based on the following distinction: time-continuous nonlinear differential equations ? time-discrete maps One approach starts from time-continuous differential equations and leads to time-discrete maps, which are obtained from them by a suitable discretization of time. This path is pursued, e.g., in the book by Strogatz [Str94]. 1 The other approach starts from the study of time-discrete maps and then gradually builds up to time-continuous differential equations, see, e.g., [Ott93, All97, Dev89, Has03, Rob95]. After a short motivation in terms of nonlinear differential equations, for the rest of this course we shall follow the latter route to dynamical systems theory. This allows a generally more simple way of introducing the important concepts, which can usually be carried over to a more complex and physically realistic context.
標(biāo)簽： Systems_Rainer Introduction Dynamical Klages to
上傳時(shí)間： 2020-06-10
上傳用戶：shancjb
This book is an outgrowth of a course developed at Stanford University over the past five years. It is suitable as a self-contained textbook for second-level undergraduates or for first-level graduate students in almost every field that employs quantitative methods. As prerequisites, it is assumed that the student may have had a first course in differential equations and a first course in linear algebra or matrix analysis. These two subjects, however, are reviewed in Chapters 2 and 3, insofar as they are required for later developments.
標(biāo)簽： Introduction_to_Dynamic_Systems
上傳時(shí)間： 2020-06-10
上傳用戶：shancjb
n recent years, there have been many books published on power system optimization. Most of these books do not cover applications of artifi cial intelligence based methods. Moreover, with the recent increase of artifi cial intelligence applications in various fi elds, it is becoming a new trend in solving optimization problems in engineering in general due to its advantages of being simple and effi cient in tackling complex problems. For this reason, the application of artifi cial intelligence in power systems has attracted the interest of many researchers around the world during the last two decades. This book is a result of our effort to provide information on the latest applications of artifi cial intelligence to optimization problems in power systems before and after deregulation.
標(biāo)簽： Intelligence Artificial System Power in
上傳時(shí)間： 2020-06-10
上傳用戶：shancjb
A kinematically redundant manipulator is a serial robotic arm that has more independently driven joints than are necessary to define the desired pose (position and orientation) of its end-effector. With this definition, any planar manipulator (a manipulator whose end-effector motion is restrained in a plane) with more than three joints is a redundant manipulator. Also, a manipulator whose end-effector can accept aspatialposeisaredundant manipulator ifithas morethan sixindependently driven joints. For example, the manipulator shown in Fig. 1.1 has two 7-DOF arms mounted on a torso with three degrees of freedom (DOFs). This provides 10 DOFs for each arm. Since the end-effector of each arm can have a spatial motion with six DOFs, the arms are redundant.
標(biāo)簽： Autonomous Modeling Planning Robots Path
上傳時(shí)間： 2020-06-10
上傳用戶：shancjb
Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propa- gation. Similarly, new models based on kernels have had significant impact on both algorithms and applications.
標(biāo)簽： Bishop-Pattern-Recognition-and-Ma chine-Learning
上傳時(shí)間： 2020-06-10
上傳用戶：shancjb
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