[IEICE-CS eNews<2008-13>] USN研チュートリアル「Signal Processing for Sensor Networks」開催案内

May 8, 2008

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http://u-netlab.jp/ja/node/189

演題：Signal Processing for Sensor Networks
講師：Jose M. F. Moura (Carnegie Mellon University)
日時：平成20年6月13日（金）13:00ー17:30
会場：慶應義塾大学矢上校舎厚生棟大会議室

申込み
聴講料：無料
定員：100名（申込締切日までの先着順）
申込締切日：平成20年6月8日
申込方法：こちら http://u-netlab.jp/ja/node/190

Abstract:
We focus on distributed inference, like detection,
estimation, or classification in sensor networks. Sensor
networks usually have a large number of sensors that monitor
continuously the state of a possibly large scale system and
collect large amounts of data.  The sensors are usually
inexpensive and operate under limited power, communication,
and computational resources. Issues of interest include
distributed localization, resource allocation, distributed,
and tradeoffs among resource parameters like bandwidth and
power. Many of these problems employ a consensus algorithm,
which is an iterative distributed algorithm. The lectures
will study the consensus algorithm and conditions for its
convergence under a wide broad set of network conditions ?
deterministic or random networks, i.e., networks where
communication links or channels may fail at random times,
noiseless or noisy channels, analog or digital (quantized)
communications.

Contents:
    1. Sensor networks: illustrative discussion of
       technologies, architectures, and applications
    2. Problems of interest:
        a. Localization
        b. Distributed inference
            i.  Distributed estimation
            ii. Distributed detection
    3. Background on graphs and spectral graph concepts
    4. Consensus algorithm
        a. Definition
        b. Convergence
    5. Sensor network models
    6. Network design
    7. Distributed estimation algorithms
    8. Distributed localization
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