Weighted finite automata are classical nondeterministic finite
automata in which the transitions carry weights. These weights may
model, for example, the cost involved when executing a transition,
the resources or time needed for this, or the probability or
reliability of its successful execution. Weights can also be added
to classical automata with infinite state sets like pushdown
automata, and this extension constitutes the general concept of
weighted automata. Since their introduction in the 1960s they have
stimulated research in related areas of theoretical computer
science, including formal language theory, algebra, logic, and
discrete structures. Moreover, weighted automata and weighted
context-free grammars have found application in natural-language
processing, speech recognition, and digital image compression.
This book covers all the main aspects of weighted automata and
formal power series methods, ranging from theory to applications.
The contributors are the leading experts in their respective areas,
and each chapter presents a detailed survey of the state of the art
and pointers to future research. The chapters in Part I cover the
foundations of the theory of weighted automata, specifically
addressing semirings, power series, and fixed point theory. Part II
investigates different concepts of weighted recognizability. Part
III examines alternative types of weighted automata and various
discrete structures other than words. Finally, Part IV deals with
applications of weighted automata, including digital image
compression, fuzzy languages, model checking, and natural-language
processing.
Computer scientists and mathematicians will find this book an
excellent survey and reference volume, and it will also be a
valuable resource for students exploring this exciting research
area.
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