Moreover frequency detection, the core of the third part, is analyzed in detail and based on the complex magnitude of harmonic signal, a novel algorithm for computing the frequency deviation in real-time is proposed.

Based on the complex magnitude of harmonic signals and under the condition of ideal synchronous samplings, an algorithm for computing the frequency deviation is proposed.

A detection algorithm is derived to implement radar target detection through the Rao test with known Doppler frequency shift and unknown complex amplitude of the correlated noise,which is assumed as an autoregressive(AR) model.

A function of synchronous superposition of object complex amplitude reconstructed from N-step phase-shifting through one integral period (N-step phase-shifting function for short) was proposed.

In ideal conditions, the proposed method is a kind of synchronous superposition algorithm in which the complex amplitude is separated, measured and superposed.

A general nonlinear parabolic equation for the complex amplitude of excitation is derived by reduction of the Oregonator, the Field-Noyes model of the Belousov-Zhabotinskii reaction, with allowance made for diffusion.

A general nonlinear parabolic equation for the complex amplitude of excitation is derived by reduction of the Oregonator, the Field-Noyes model of the Belousov-Zhabotinskii reaction, with allowance made for diffusion.

The complex amplitude transmittance and reflectance are found for the entire multilayered structure from the calculated matrix elements.

The computation of Green's function in spatial domain is the key difficulty in solving multilayer structure. According to the nonuniqueness of inverse problem, a novel method based on discrete complex image method(DCIM)-fixed real image method(FRIM) is put forward.According to this method, we use fixed images at real instead of complex locations to approximate the spectral Green's function, the images real locations are selected according to the classic image theory, and the complex amplitudes can be obtained...

The computation of Green's function in spatial domain is the key difficulty in solving multilayer structure. According to the nonuniqueness of inverse problem, a novel method based on discrete complex image method(DCIM)-fixed real image method(FRIM) is put forward.According to this method, we use fixed images at real instead of complex locations to approximate the spectral Green's function, the images real locations are selected according to the classic image theory, and the complex amplitudes can be obtained using simple point match method. This method is simpler and faster than the complex image method for avoiding the fitting procedure of Prony or GPOF. A group of computation results are given and validated by DCIM.

First, the reason for spectrum leakage and its influence to DFT used in frequency analysis is introduced. Based on the complex magnitude of harmonic signals and under the condition of ideal synchronous samplings, an algorithm for computing the frequency deviation is proposed. Second, this algorithm is further modified according to actual sampling and the power network signals. Finally, the iterative formulas for real-time determination of power network frequency are presented as well. Simulation results show...

First, the reason for spectrum leakage and its influence to DFT used in frequency analysis is introduced. Based on the complex magnitude of harmonic signals and under the condition of ideal synchronous samplings, an algorithm for computing the frequency deviation is proposed. Second, this algorithm is further modified according to actual sampling and the power network signals. Finally, the iterative formulas for real-time determination of power network frequency are presented as well. Simulation results show that the algorithm can follow up the frequency deviation accurately and quickly. Moreover, the algorithm will be of potential applications in the fields of AC real-time determination due to its features of less computation time, fast convergence and ability of against harmonic interference.

A detection algorithm is derived to implement radar target detection through the Rao test with known Doppler frequency shift and unknown complex amplitude of the correlated noise,which is assumed as an autoregressive(AR) model.The unknown parameters are estimated by maximum likelihood estimation under hypothesis H_0.It is shown through computer simulations that the algorithms has almost the same performance as that of the GLRT,while the structure is simpler.The asymptotic performance of the algorithms is also...

A detection algorithm is derived to implement radar target detection through the Rao test with known Doppler frequency shift and unknown complex amplitude of the correlated noise,which is assumed as an autoregressive(AR) model.The unknown parameters are estimated by maximum likelihood estimation under hypothesis H_0.It is shown through computer simulations that the algorithms has almost the same performance as that of the GLRT,while the structure is simpler.The asymptotic performance of the algorithms is also given.