Dylan McDonald

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Outlier detection is a well studied problem in various fields. The unique challenges of wireless sensor networks such as limited bandwidth, memory, energy, and unreliable communi- cation make this problem especially difficult. Sensors can detect outliers for a plethora of reasons and these reasons need to be inferred in real time. Here, we present a new(More)
Outlier detection is a well studied problem in various fields. The unique characteristics and constraints of wireless sensor networks (WSN) make this problem especially challenging. Sensors can detect outliers for a plethora of reasons and these reasons need to be inferred in real time. Here, we survey the current state of research in this area, compare(More)
Outlier detection is a well studied problem in various fields. The unique challenges of wireless sensor networks make this problem especially challenging. Sensors can detect outliers for a plethora of reasons and these reasons need to be inferred in real time. Here, we present a new communication technique to find outliers in a wireless sensor network.(More)
We are considering a discrete-time model of an access ATM switch with output buuers. A switch with output queueing has an optimum performance, however it requires a switch fabric with speed of N. However, The switch fabric may operate L < N times the speed of the input/output links. Also random traac assumption underestimates the buuer size. In our study,(More)
A self-training visual inspection system using a connectionist classifier is presented. The system is composed of a control unit, a signal-processing unit, and a connectionist classifier. The control unit both generates the training set and performs the function of teacher to the classifier. The second unit compresses the two-dimensional image into a(More)
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