Scattering centers extracted from radar returns are features that can be used for automatic target recognition (ATR). Many diierent algorithms exist which can extract scattering centers from a radar return. They all, however, fall into one of two large classes: model and FFT-based techniques. In this paper, we consider one FFT and two model based techniques: 1) FFT with peak extraction, 2) the ...

Autoregressive Moving average (ARMA) is a parametric based method of signal representation. It is suitable for problems in which the signal can be modeled by explicit known source functions with a few adjustable parameters. Various methods have been suggested for the coefficients determination among which are Prony, Pade, Autocorrelation, Covariance and most recently, the use of Artificial Neur...

Common-acoustic-poles/zeros (CAPZ) approximation is a more efficient way to model head-related transfer functions (HRTF’s). In CAPZ approximation, a group of HRTF’s can share a set of poles but use their own zeros. Previous CAPZ works, such as the Prony, Shanks and iterative prefiltering methods, were all based on the linearized least-square criterion. A new state-space approach, jointly balanc...

in this paper, we propose a new residual analysis method using fourier series transform into fuzzy time series model for improving the forecasting performance. this hybrid model takes advantage of the high predictable power of fuzzy time series model and fourier series transform to fit the estimated residuals into frequency spectra, select the low-frequency terms, filter out high-frequency term...

The diagnosis of gearbox faults based on the Fourier analysis of the vibration signal produced from a gear reductor system has proved its limitations in terms of spectral resolution. In this paper, we propose a method for the fault diagnosis of a gear reductor made of two toothed wheels operating at constant conditions. This technique is based on Prony method. The good performances of the propo...

To damp the oscillations in a power system, a new intelligent controller is proposed. This controller is an online trained wavelet neural network controller (OTWNNC) in which adaptive learning rates derived by the Lyapunov stability are employed to guarantee the convergence of the proposed controller. During the online control process, the identification of system is not necessary, because of l...