Image Processing Reference
In-Depth Information
9
Distributed Signal Processing
in Sensor Networks
.
Introduction .........................................
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Notation
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Case Study: Spectrum Analysis Using
SensorNetworks .....................................
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Background
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Estimating the Power Spectrum of a Signal
Source Using Sensor Network Data
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InverseandIll-PosedProblems.......................
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Ill-Posed Linear Operator Equations
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Regularization
Methods for Solving Ill-Posed Linear Operator Equations
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Spectrum Estimation Using Generalized
Projections...........................................
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Distributed Algorithms for Calculating Generalized
Projection............................................
Omid S. Jahromi
Sonavation Inc.
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Ring Algorithm
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Star Algorithm
. Conclusion...........................................
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Parham Aarabi
University of Toronto
References .................................................
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9.1 Introduction
Imagine a networked sensing system with thousands or millions of independent components, all
capable of generating and communicating the data. A sensing system of such complexity would seem
unthinkable a few decades ago but, today, it has become a possibility, thanks to the widespread avail-
ability of cheap embedded processors and easily accessible wireless networks. Networking a large
number of autonomous sensing devices is an emerging technology that promises an unprecedented
ability to monitor the physical word via a spatially distributed network of small, inexpensive, wireless
devices that have the ability to self-organize in a well-connected network. A wide range of applications
of sensor networks are being envisioned in a number of areas, including geographical monitoring,
inventory management, homeland security, and health care.
The building blocks of a sensor network, often called “Motes,” are self-contained, battery-powered
computers that measure light, sound, temperature, humidity, and other environmental variables
(Figure .). Motes are inevitably constrained in processing speed, storage capacity, and communi-
cation bandwidth. Additionally, their lifetime is determined by their ability to conserve power.
Inprinciple,adistributednetworkofsensorscanbehighlyscalable,costefective,androbust
with respect to individual Mote's failure. However, there are many technological hurdles that must
be overcome for sensor networks to become viable. Motes are inevitably constrained in processing