Linear canonical transform is an integral transform with four parameters and has been proved to be powerful tool for optics, radar system analysis, filter design etc. Fractional Fourier transform and Fresnel transform can be seen as a special case of linear canonical transform with real parameters. Further generalization of linear canonical transform with complex parameters is also developed an...

A discrete-time variable structure controller for aircraft elevator control using the method for control of plants with finite zeros in canonical subspace is proposed in this paper. First, a discrete mathematical model of the system over canonical space, using the delta transform, is given. Then, decomposition of the canonical space to subspaces with and without control is carried out by introd...

In this paper, we generalize the windowed Fourier transform to the windowed linear canonical transform by substituting the Fourier transform kernel with the linear canonical transform kernel in the windowed Fourier transform definition. It offers local contents, enjoys high resolution, and eliminates cross terms. Some useful properties of the windowed linear canonical transform are derived. Tho...

one of the most common signals used for achieving high range resolution in radar is stepped-frequency signals. when a target is stationary in these radars, dft (discrete fourier transform) based processing is used to attain high range resolution profile (hrrp). however, in the case of moving target, due to spreading of the echo signal spectrum, dft based processing is not optimal and decreases ...

For the efficient identification of quantum states, we propose notion linear canonical wavelet transform in framework mechanics. Using machinery Dirac representation theory and integration within an ordered product operators, recast to a matrix element squeezing–displacing operator U(?,s)KM between analyzing vector ??| two-mode state |f? be transformed. We also derive inner relation inversion f...

The windowed offset linear canonical transform (WOLCT) can be identified as a generalization of the (WLCT). In this paper, we generalize several different uncertainty principles for WOLCT, including Heisenberg principle, Hardy’s Donoho–Stark’s principle and Nazarov’s principle. Finally, application analogues Poisson summation formula sampling formulas are given.