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IPSN
2004
Springer
13 years 10 months ago
Estimation from lossy sensor data: jump linear modeling and Kalman filtering
Due to constraints in cost, power, and communication, losses often arise in large sensor networks. The sensor can be modeled as an output of a linear stochastic system with random...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal
CDC
2010
IEEE
110views Control Systems» more  CDC 2010»
12 years 11 months ago
Synthesis of embedded control systems with high sampling frequencies
Motivated by current technological advances in the design of real-time embedded systems, this work deals with the digital control of a continuous-time linear time-invariant (LTI) s...
Javad Lavaei, Somayeh Sojoudi, Richard M. Murray
ICASSP
2011
IEEE
12 years 8 months ago
Adaptive recursive FLANN filters for nonlinear active noise control
In this paper, a recursive nonlinear filter exploiting trigonometric expansions of the past output samples is introduced. Its peculiarity is, in general, the ability to model rea...
Giovanni L. Sicuranza, Alberto Carini
IEAAIE
2005
Springer
13 years 10 months ago
Movement Prediction from Real-World Images Using a Liquid State Machine
Prediction is an important task in robot motor control where it is used to gain feedback for a controller. With such a self-generated feedback, which is available before sensor rea...
Harald Burgsteiner, Mark Kröll, Alexander Leo...