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Paper data
Nonlinear prediction of infrared data by the Wiener system

Bernabeu Pablo, Universidad Politécnica de Valencia
Vegara Luís, Universidad Politécnica de Valencia
Bosch Ignacio, Universidad Politécnica de Valencia

Page numbers in the proceedings:
Volume I pp 309-312

Nonlinear Signal and Systems / Adaptive Methods

Paper abstract
We consider the use of the Wiener system to perform nonlinear prediction. In this paper we propose a technique to retain the simplicity of the linear prediction by including a memoryless nonlinear function. The design of this later is approached from a Bayesian perspective: we look for the conditional mean of the predicted value, given the output of the linear predictor. Two techniques are proposed: the first one makes use of a closed form solution where some higher-order statistics are to be estimated. The second one is a direct sample estimate of the conditional mean given a data training set. The techniques are applied to improve the signal to noise ratio in the automatic detection of fire by infrared signal processing.

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