In this study; medical images were denoising with multiresolution analyses using real-valued wavelet transform (RVWT), complex-valued wavelet transform (CVWT), ridgelet transform (RT), real-valued first-generation curvelet transform (RVFG CT), real-valued second-generation curvelet transform (RVSG CT), complex-valued second-generation curvelet transform (CVSG CT) and results are compared. First...

This research studied the effect of additive and multiplicative noise in images, and their solution. Salt n pepper, and Gaussian noise is considered as a additive noise, while impulsive noise is considered as a multiplicative noise. For additive noise, this paper presents the outcome of Wiener filter, and Pseudo inverse filter, while for impulsive noise, we studied wavelet denoising. A hybrid f...

In this paper we show that any sequence of infinite lattice constellations which is good for the unconstrained Gaussian channel can be shaped into a capacity-achieving sequence of codes for the power-constrained Gaussian channel under lattice decoding and non-uniform signalling. Unlike previous results in the literature, our scheme holds with no extra condition on the lattices (e.g. quantizatio...

Abstract We consider a real continuous-time bandlimited additive white Gaussian noise channel with 1-bit output quantization. On such the information is carried by temporal distances of zero-crossings transmit signal. derive an approximate lower bound on capacity lower-bounding mutual rate for input signals exponentially distributed zero-crossing distances, sine-shaped transition waveform, and ...

in this paper, a new approach based on game theory has been proposed to multi responses problem optimization. game theory is a useful tool for decision making in the conflict of interests between intelligent players in order to select the best joint strategy for them through selecting the best joint desirability. present research uses the game theory approach via definition of each response as ...

In the context of ridge regression, the estimation of ridge (shrinkage) parameter plays an important role in analyzing data. Many efforts have been put to develop skills and methods of computing shrinkage estimators for different full-parametric ridge regression approaches, using eigenvalues. However, the estimation of shrinkage parameter is neglected for semiparametric regression models. The m...