Reinforcement learning (RL) algorithms provide a sound theoretical basis for building learning control architectures for embedded agents. Unfortunately all of the theory and much ...
Satinder P. Singh, Tommi Jaakkola, Michael I. Jord...
—A practical system approach for time-multiplexing cellular neural network (CNN) implementations suitable for processing large and complex images using small CNN arrays is presen...
The architecture of two-tiered sensor networks, where storage nodes serve as an intermediate tier between sensors and a sink for storing data and processing queries, has been widel...
Many systems such as Tukwila and YFilter combine automaton and algebra techniques to process queries over tokenized XML streams. Typically in this architecture, an automaton is fi...
—Sensor processing is a common task within many embedded system domains, such as in control systems, the sensor feedback is used for actuator control. In this paper we have surve...