A new concept of a quantum-like mixture model is introduced. It describes the distribution with assumption that point generated by each Gaussian at same time. The improves classification accuracy in machine learning indicating uncertain points should not be assigned to any class. increases on iris data set from 96.67 99.24%.

Hydrograph modeling and prediction of groundwater levels are the main concerns of most hydrogeological calculations and water resource management process. The present study is an application of Sequential Gaussian Simulation (SGSim) method for predicting groundwater levels using recorded monthly data (180 months) related to 21 piezometers of Behbahan aquifer, southwest of Iran. To generate real...

Sparse coding aims to model data vectors as sparse linear combinations of basis elements, but a majority related studies are restricted continuous without spatial or temporal structure. A new model-based (MSC) method is proposed provide an effective and flexible framework for learning features from different types: continuous, discrete, categorical, modeling types correlations: temporal. The sp...

There are many unavoidable noise interferences in image acquisition and transmission. To make it better for subsequent processing, the noise in the image should be removed in advance. There are many kinds of image noises, mainly including salt and pepper noise and Gaussian noise. This paper focuses on the research of the Gaussian noise removal. It introduces many wavelet threshold denoising alg...

In this paper, we derive a capacity inner bound for a synchronous Gaussian Z channel with intersymbol interference (ISI) under input power constraints. This is done by converting the original channel model into an n-block memoryless circular Gaussian Z channel (n-CGZC) and successively decomposing the n-block memoryless channel into a series of independent parallel channels in the frequency dom...

A detector for the case of a radar target with known Doppler and unknown complex amplitude in complex Gaussian noise with unknown parameters has been derived. The detector assumes that the noise is an Auto-Regressive (AR) process with Gaussian autocorrelation function which is a suitable model for ground clutter in most scenarios involving airborne radars. The detector estimates the unknown...