Monte Carlo Algorithm for Least Dependent Non-Negative Mixture Decomposition

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Monte Carlo Algorithm for Least Dependent Non-Negative Mixture Decomposition

We propose a simulated annealing algorithm (stochastic non-negative independent component analysis, SNICA) for blind decomposition of linear mixtures of non-negative sources with non-negative coefficients. The demixing is based on a Metropolis-type Monte Carlo search for least dependent components, with the mutual information between recovered components as a cost function and their non-negativ...

متن کامل

Spectral Mixture Decomposition by Least Dependent Component Analysis

A recently proposed mutual information based algorithm for decomposing data into least dependent components (MILCA) is applied to spectral analysis, namely to blind recovery of concentrations and pure spectra from their linear mixtures. The algorithm is based on precise estimates of mutual information between measured spectra, which allows to assess and make use of actual statistical dependenci...

متن کامل

Monte Carlo Simulations for Spinodal Decomposition

This paper addresses the phenomenon of spinodal decomposition for the CahnHilliard equation. Namely, we are interested in why most solutions to the CahnHilliard equation which start near a homogeneous equilibrium u0 in the spinodal interval exhibit phase separation with a characteristic wavelength when exiting a ball of radius R. There are two mathematical explanations for spinodal decompositio...

متن کامل

Monte Carlo Dose Algorithm

Conventional dose calculation algorithms, such as Pencil Beam are proven effective for tumors located in homogeneous regions with similar tissue consistency such as the brain. However, these algorithms tend to overestimate the dose distribution in extracranial regions such as in the lung and head and neck regions where large inhomogeneities exist. Due to the inconsistencies seen in current calc...

متن کامل

Bayesian Mixture Modeling by Monte Carlo Simulation

It is shown that Bayesian inference from data modeled by a mixture distribution can feasibly be performed via Monte Carlo simulation. This method exhibits the true Bayesian predictive distribution, implicitly integrating over the entire underlying parameter space. An innnite number of mixture components can be accommodated without diiculty, using a prior distribution for mixing proportions that...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Analytical Chemistry

سال: 2006

ISSN: 0003-2700,1520-6882

DOI: 10.1021/ac051707c