Models for Distributed Computing in Grid Sensor Networks

Using local state space models, a method for distributed information processing in rectangular grid sensor networks is presented. Non-linear systems and signal processing algorithms are represented in a local state space model. Then the local state space model is implemented on the sensor network. The local state space models used are generalizations of Fornasini-Marchesini and Givone-Roesser models for linear time-invariant 3-D systems. Realtime implementation issues of the said method are also discussed.

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