Similarly, the fractional Fourier spectrum of periodic nonuniformly sampled signals and the fractional spectral reconstruction are discussed by Ran Tao [14, 15], for linear frequency modulation (LFM) signals.
Equation (6) reveals the relationship between AF and FRFT as follows: the slice of AF at angle in the ambiguity plane is the Fourier transform of the fractional power spectrum of angle.
They can be estimated from the peak position of its fractional Fourier spectrum as follows α ^, u ^ = arg max α, u X α u 2 f ^ dc = u ^ csc α ^ k ^ d = - cot α ^. (14).
According to the equivalence relationship between RWT and the fractional power spectrum [13, 14], a LFM-signal detection and parameters estimation method based on FRFT has been presented [10, 11], which achieves a near-RWT performance at much lower computational complexity.
The fractional biodiversity spectrum has a peak at 31.9±1.0 Myr at the 0.1 confidence level.
The obtained spectra are multiplexed together to what is called as the encrypted fractional joint power spectrum (EFJPS).
The results are analyzed in terms of power spectra, fractional Brownian motion theory and confocal image processing.
SMA estimates the fractional abundance of spectra representing physically meaningful materials, known as spectral endmembers, which comprise a mixed pixel, thus providing sub-pixel estimates of surface water extent.
Viable inter-cell interference mitigation approaches are reviewed in [2], including the use of power control, fractional frequency reuse, opportunistic spectrum access, intra and inter-cell interference cancellation, and multiple input multiple output (MIMO) techniques.
