The continuing vitality of spread-spectrum communication systems and the devel-
opment of new mathematICAl methods for their analysis provided the motivation to
undertake this new edition of the book. This edition is intended to enable readers
to understand the current state-of-the-art in this field. Almost twenty percent of the
materialinthiseditionisnew, includingseveralnewsections, anewchapteronadap-
tive arrays and filters, and a new chapter on code-division multiple-access networks.
Since the first edition of the book was published, the field of modeling and simulation of
communication systems has grown and matured in many ways, and the use of simulation as a
day-to-day tool is now even more common practice. Many new modeling and simulation
approaches have been developed in the recent years, many more commercial simulation
packages are available, and the evolution of powerful general mathematICAl applications
packages has provided still more options for computer-aided design and analysis. With the
current interest in digital mobile communications, a primary area of application of modeling
and simulation is now to wireless systems of a different flavor than the traditional ones.
The continuing vitality of spread-spectrum communication systems and the devel-
opment of new mathematICAl methods for their analysis provided the motivation to
undertake this new edition of the book. This edition is intended to enable readers
to understand the current state-of-the-art in this field. Almost twenty percent of the
materialinthiseditionisnew, includingseveralnewsections, anewchapteronadap-
tive arrays and filters, and a new chapter on code-division multiple-access networks.
The remainder of the material has been thoroughly revised, and I have removed a
considerable amount of material that has been superseded by more definitive results.
Striking developments have taken place since 1980 in feedback control theory. The subject has be-
come both more rigorous and more applicable. The rigor is not for its own sake, but rather that even
in an engineering discipline rigor can lead to clarity and to methodical solutions to problems. The
applicability is a consequence both of new problem formulations and new mathematICAl solutions
to these problems. Moreover, computers and software have changed the way engineering design is
done. These developments suggest a fresh presentation of the subject, one that exploits these new
developments while emphasizing their connection with classical control.
Mathematics isplayinganevermoreimportantroleinthephysicalandbiological
sciences,provokinga blurringof boundariesbetweenscientific disciplinesand a
resurgenceof interestinthemodemas well as theclassicaltechniquesof applied
mathematics. Thisrenewalofinterest,bothinresearchandteaching,hasledtothe
establishment of theseries: Texts in AppliedMathematics (TAM).
Thedevelopmentofnewcoursesisanaturalconsequenceofahighleve
The purpose of this preface is twofold. Firstly, to give an informal historical
introduction to the subject area of this book, Systems and Control, and
secondly, to explain the philosophy of the approach to this subject taken
in this book and to outline the topics that will be covered.
This introductory chapter is devoted to reviewing the fundamental ideas of
control from a multivariable point of view. In some cases, the mathematics
and operations on systems (modelling, pole placement, etc.), as previously
treated in introductory courses and textbooks, convey to the readers an un-
realistic image of systems engineering. The simplifying assumptions, simple
examples and “perfect” model set-up usually used in these scenarios present
the control problem as a pure mathematICAl problem, sometimes losing the
physical meaning of the involved concepts and operations. We try to empha-
sise the engineering implication of some of these concepts and, before entering
into a detailed treatment of the different topics, a general qualitative overview
is provided in this chapter.
Computer science as an academic discipline began in the 1960’s. Emphasis was on
programming languages, compilers, operating systems, and the mathematICAl theory that
supported these areas. Courses in theoretical computer science covered finite automata,
regular expressions, context-free languages, and computability. In the 1970’s, the study
of algorithms was added as an important component of theory. The emphasis was on
making computers useful. Today, a fundamental change is taking place and the focus is
more on a wealth of applications. There are many reasons for this change. The merging
of computing and communications has played an important role. The enhanced ability
to observe, collect, and store data in the natural sciences, in commerce, and in other
fields calls for a change in our understanding of data and how to handle it in the modern
setting. The emergence of the web and social networks as central aspects of daily life
presents both opportunities and challenges for theory.
This edition of Digital Image Processing is a major revision of the book. As in
the 1977 and 1987 editions by Gonzalez and Wintz, and the 1992, 2002, and 2008
editions by Gonzalez and Woods, this sixth-generation edition was prepared
with students and instructors in mind. The principal objectives of the book
continue to be to provide an introduction to basic concepts and methodologies
applicable to digital image processing, and to develop a foundation that can
be used as the basis for further study and research in this field. To achieve
these objectives, we focused again on material that we believe is fundamental
and whose scope of application is not limited to the solution of specialized
problems. The mathematICAl complexity of the book remains at a level well
within the grasp of college seniors and first-year graduate students who have
introductory preparation in mathematICAl analysis, vectors, matrices, probability,
statistics, linear systems, and computer programming. The book website provides
tutorials to support readers needing a review of this background material
ets gre 數學考試講義，
mathematICAl Conventions for the Quantutative Reasoning Measure of the GRE revised General Test
for the Quantitative Reasoning Measure of the GRE? revised General Test
