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IPSN
2004
Springer
13 years 11 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
2009
IEEE
221views Control Systems» more  CDC 2009»
13 years 10 months ago
Parametrization invariant covariance quantification in identification of transfer functions for linear systems
This paper adresses the variance quantification problem for system identification based on the prediction error framework. The role of input and model class selection for the auto-...
Tzvetan Ivanov, Michel Gevers
CDC
2010
IEEE
129views Control Systems» more  CDC 2010»
13 years 1 months ago
On optimal input signal design for frequency response estimation
This paper studies optimal input excitation design for parametric frequency response estimation. We will focus on least-squares estimation of Finite Impulse Response (FIR) models a...
Bo Wahlberg, Håkan Hjalmarsson, Petre Stoica
TRANSCI
2010
128views more  TRANSCI 2010»
13 years 4 months ago
An Information-Theoretic Sensor Location Model for Traffic Origin-Destination Demand Estimation Applications
To design a transportation sensor network, the decision-maker needs to determine what sensor investments should be made, as well as when, how, where and with what technologies. Th...
Xuesong Zhou, George F. List
PROMISE
2010
13 years 1 months ago
Modeling the relationship between software effort and size using deming regression
Background: The relation between software effort and size has been modeled in literature as exponential, in the sense that the natural logarithm of effort is expressed as a linear...
Nikolaos Mittas, Makrina Viola Kosti, Vasiliki Arg...