Title :
Signal detection using approximate Karhunen-Loeve expansions
Author :
Ruiz-Molina, Jaun Carlos ; Navarro-Moreno, Jesús ; Oya, Antonia
Author_Institution :
Dept. of Stat. & Oper. Res., Jaen Univ., Spain
fDate :
5/1/2001 12:00:00 AM
Abstract :
A new approach to the signal detection problem in continuous time is presented on the basis of approximate Karhunen-Loeve (K-L) expansions. This methodology gives approximate solutions to the problem of detecting either deterministic or Gaussian signals in Gaussian noise. Furthermore, for this last problem an approximate estimator-correlator representation is provided which approaches the optimum detection statistic
Keywords :
Gaussian noise; Karhunen-Loeve transforms; continuous time systems; estimation theory; interference (signal); least mean squares methods; signal detection; signal representation; Gaussian noise; Gaussian signals; approximate Karhunen-Loeve expansions; approximate estimator-correlator representation; continuous time; deterministic signals; minimum mean square error estimator; optimum detection statistic; signal detection; Additive white noise; Eigenvalues and eigenfunctions; Gaussian noise; Integral equations; Kernel; Random processes; Signal detection; State estimation; Statistics; Stochastic resonance;
Journal_Title :
Information Theory, IEEE Transactions on
