This book provides an introduction to decision making in a distributedcomputational framework. When most computations were performed by a centralprocessor class... » 

This book provides an introduction to decision making in a distributedcomputational framework. When most computations were performed by a centralprocessor classical detection theory could assume that the processor couldmake decisions based on complete information. The development of distributedprocessors working in parallel on different parts of the same computationalproblem makes it necessary to make local decisions that are then conveyed toother processors where ultimately a fusion center must make global decisions.Using numerous examples throughout the book the author discusses suchdistributed detection processes under various different formulations and in awide variety of network topologies. By providing a unified treatment of therecent advances this book should prove valuable not only to researchers activein the field but also to graduate students and others embarking on research indetection signal processing and statistical decision theory. Some priorknowledge of detection theory is assumed. «