demo_CreateLPAKernels.m
LPA kernel design
Calculates the LPA convolution smoothing and differentiation
kernels of polynomial approximation and its frequency response characteristic, and draws them.



demo_LPAICI_1D.m
LPAICI denoising
Performs the Anisotropic LPAICI denoising on observations which are contaminated by additive white Gaussian noise.



demo_MedianICI_1D.m
MedianICI denoising
Performs the Anisotropic MedianICI denoising on observations which are contaminated by the additive white Gaussian and impulsive noise.



demo_IdealInvariantScale1D.m
Oracle Invariant scale selection
Illustrates the problem of invariant scale selection. The invariant ideal scale
h of the LPA estimator is found for the noisy signal assuming that the true signal is known.



demo_IdealVaryinigScale1D.m
Oracle Varying scale selection
Illustrates optimal scale selection for every point of the signal.
The varying ideal scale h of the LPA estimator is found for the noisy signal assuming that the true signal is known.
Ideal scale is selected by minimization of mean square error in a pointwise manner.


