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The second edition of this textbook provides a fully updated
approach to fuzzy sets and systems that can model uncertainty -
i.e., "type-2" fuzzy sets and systems. The author demonstrates how
to overcome the limitations of classical fuzzy sets and systems,
enabling a wide range of applications from time-series forecasting
to knowledge mining to control. In this new edition, a bottom-up
approach is presented that begins by introducing classical (type-1)
fuzzy sets and systems, and then explains how they can be modified
to handle uncertainty. The author covers fuzzy rule-based systems -
from type-1 to interval type-2 to general type-2 - in one volume.
For hands-on experience, the book provides information on accessing
MatLab and Java software to complement the content. The book
features a full suite of classroom material.
This book explores recent developments in the theoretical
foundations and novel applications of general and interval type-2
fuzzy sets and systems, including: algebraic properties of type-2
fuzzy sets, geometric-based definition of type-2 fuzzy set
operators, generalizations of the continuous KM algorithm,
adaptiveness and novelty of interval type-2 fuzzy logic
controllers, relations between conceptual spaces and type-2 fuzzy
sets, type-2 fuzzy logic systems versus perceptual computers;
modeling human perception of real world concepts with type-2 fuzzy
sets, different methods for generating membership functions of
interval and general type-2 fuzzy sets, and applications of
interval type-2 fuzzy sets to control, machine tooling, image
processing and diet. The applications demonstrate the
appropriateness of using type-2 fuzzy sets and systems in real
world problems that are characterized by different degrees of
uncertainty.
This book explores recent developments in the theoretical
foundations and novel applications of general and interval type-2
fuzzy sets and systems, including: algebraic properties of type-2
fuzzy sets, geometric-based definition of type-2 fuzzy set
operators, generalizations of the continuous KM algorithm,
adaptiveness and novelty of interval type-2 fuzzy logic
controllers, relations between conceptual spaces and type-2 fuzzy
sets, type-2 fuzzy logic systems versus perceptual computers;
modeling human perception of real world concepts with type-2 fuzzy
sets, different methods for generating membership functions of
interval and general type-2 fuzzy sets, and applications of
interval type-2 fuzzy sets to control, machine tooling, image
processing and diet. The applications demonstrate the
appropriateness of using type-2 fuzzy sets and systems in real
world problems that are characterized by different degrees of
uncertainty.
The First Conference on Engineering Probability in Flood Defense
was orga nized by the Department of Mathematics and Informatics of
the Delft U niver sity of Technology and the Department of
Industrial Engineering and Opera tions Research of the University
of California at Berkeley, and was held on June 1,2 1995 in Delft.
Groups at Berkeley and Delft were both deeply engaged in modeling
deterioration in civil structures, particularly flood defense
structures. The plans for the conference were well under way when
the dramatic floods in The Netherlands and California in the winter
of 1994-1995 focused world attention on these problems. The design
of civil engineering structures and systems is essentially an
example of decision making under uncertainty. Although the decision
making part of the process is generally acknowledged, the
uncertainty in variables and param eters in the design problem is
less frequently recognized. In many practical design procedures the
uncertainty is concealed behind sharp probabilistic de sign targets
like 'once in a thousand years' combined with a standardized use of
safety factors. The choice of these probabilistic design targets,
however, is based on an assessment of the uncertainty of the
variable under consideration, and on its assessed importance. The
value of the safety factor is governed by similar considerations.
Standard practice is simply accu ulated experience and engineering
judgment. In light of the great number of civil engineering
structures that function suc-. cessfully, one may say that this
standard practice has proven itself broadly satisfactory."
Convolution is the most important operation that describes the
behavior of a linear time-invariant dynamical system. Deconvolution
is the unraveling of convolution. It is the inverse problem of
generating the system's input from knowledge about the system's
output and dynamics. Deconvolution requires a careful balancing of
bandwidth and signal-to-noise ratio effects. Maximum-likelihood
deconvolution (MLD) is a design procedure that handles both
effects. It draws upon ideas from Maximum Likelihood, when unknown
parameters are random. It leads to linear and nonlinear signal
processors that provide high-resolution estimates of a system's
input. All aspects of MLD are described, from first principles in
this book. The purpose of this volume is to explain MLD as simply
as possible. To do this, the entire theory of MLD is presented in
terms of a convolutional signal generating model and some
relatively simple ideas from optimization theory. Earlier
approaches to MLD, which are couched in the language of
state-variable models and estimation theory, are unnecessary to
understand the essence of MLD. MLD is a model-based signal
processing procedure, because it is based on a signal model, namely
the convolutional model. The book focuses on three aspects of MLD:
(1) specification of a probability model for the system's measured
output; (2) determination of an appropriate likelihood function;
and (3) maximization of that likelihood function. Many practical
algorithms are obtained. Computational aspects of MLD are described
in great detail. Extensive simulations are provided, including real
data applications.
The First Conference on Engineering Probability in Flood Defense
was orga nized by the Department of Mathematics and Informatics of
the Delft U niver sity of Technology and the Department of
Industrial Engineering and Opera tions Research of the University
of California at Berkeley, and was held on June 1,2 1995 in Delft.
Groups at Berkeley and Delft were both deeply engaged in modeling
deterioration in civil structures, particularly flood defense
structures. The plans for the conference were well under way when
the dramatic floods in The Netherlands and California in the winter
of 1994-1995 focused world attention on these problems. The design
of civil engineering structures and systems is essentially an
example of decision making under uncertainty. Although the decision
making part of the process is generally acknowledged, the
uncertainty in variables and param eters in the design problem is
less frequently recognized. In many practical design procedures the
uncertainty is concealed behind sharp probabilistic de sign targets
like 'once in a thousand years' combined with a standardized use of
safety factors. The choice of these probabilistic design targets,
however, is based on an assessment of the uncertainty of the
variable under consideration, and on its assessed importance. The
value of the safety factor is governed by similar considerations.
Standard practice is simply accu ulated experience and engineering
judgment. In light of the great number of civil engineering
structures that function suc-. cessfully, one may say that this
standard practice has proven itself broadly satisfactory."
The second edition of this textbook provides a fully updated
approach to fuzzy sets and systems that can model uncertainty -
i.e., "type-2" fuzzy sets and systems. The author demonstrates how
to overcome the limitations of classical fuzzy sets and systems,
enabling a wide range of applications from time-series forecasting
to knowledge mining to control. In this new edition, a bottom-up
approach is presented that begins by introducing classical (type-1)
fuzzy sets and systems, and then explains how they can be modified
to handle uncertainty. The author covers fuzzy rule-based systems -
from type-1 to interval type-2 to general type-2 - in one volume.
For hands-on experience, the book provides information on accessing
MatLab and Java software to complement the content. The book
features a full suite of classroom material.
For those who have grown tired of Christmas commercialism, who feel
Santa Claus and red-nosed reindeer do not project the true
Christmas spirit, this book may be the answer. With little-known
classics by old and new masters of the genre, this unique anthology
of Christmas stories, songs, and poems has long been a seasonal
favorite of old and young alike.
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