Signal recognition: Fourier transform vs. Hartley transform

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摘要

The new generic feature representation approach was utilized for Gaussian recognition. Approach consists of using simultaneously two new recognition features: real and imaginary Fourier components with taking into account the covariance between features.Advanced time–frequency technique, short time Fourier transform was considered.The recognition effectiveness between the new approach and Hartley based approach was compared. It was shown for Gaussian recognition that Hartley approach is not an optimal and is not even a particular case of the proposed approach. The use of the proposed approach provides an essential effectiveness gain in comparison with Hartley approach.

论文关键词:Statistical pattern recognition,Real and imaginary Fourier components,Hartley transform,Gaussian recognition,Likelihood ratio

论文评审过程:Received 1 July 2002, Revised 3 June 2003, Accepted 3 June 2003, Available online 14 August 2003.

论文官网地址:https://doi.org/10.1016/S0031-3203(03)00220-6