The spectral efficiency (channel capacity) of the optical direct-detection channel is studied. The modeling of the optical direct-detection channel as a discrete-time Poisson channel is reviewed. Closed-form integral representations for the entropy of random variables with Poisson and negative binomial distributions are derived. The spectral efficiency achievable with an arbitrary input gamma d...

in order to the enhancement of the quality of speech corrupted by additive noise, a speech enhancement method has been put forward based on the combination of spectral subtraction and binary masking. spectral subtraction is a powerful method for removing noise from speech and binary masking provides essential elements to be used in monaural speech segregation. in the proposed combined method, f...

This paper deals with the estimation of pitch from only spectral envelope information. The proposed method uses a Gaussian Mixture Model (GMM) to characterize the joint distribution of the spectral envelope parameters and pitchnormalized values. During the learning stage, the model parameters are estimated by means of the EM algorithm. Then, a regression is made which enables the determination ...

We experimentally measured the phase-matching spectral phases of aperiodic quasi-phase matched gratings for the first time (to the best of our knowledge) by nonlinear spectral interferometry. The retrieved information is useful in determining the temporal shape of the nonlinearly converted ultrafast signal and reconstructing the slowly-varying domain period distribution. The method is nondestru...

An original method of spectral similarity analysis for plagiarism detection in university project is presented. The approach is based on a clone detection tool called CLAN that performs metrics based similarity analysis of source code fragments. Definitions and algorithms for spectral similarity analysis are presented and discussed. Experiments performed on university projects are presented. Ex...

The main objective of this study is to present new method on the basis of genetic algorithms for attenuation relationship determination of horizontal peak ground acceleration and spectral acceleration. The proposed method employs the optimization capabilities of genetic algorithm to determine the coefficients of attenuation relationships of peak ground and spectral accelerations. This method ha...

I describe a Bayesian method to account for measurement errors in linear regression of astronomical data. The method allows for heteroscedastic and possibly correlated measurement errors, and intrinsic scatter in the regression relationship. The method is based on deriving a likelihood function for the measured data, and I focus on the case when the intrinsic distribution of the independent var...

In this paper an attempt has been made to develop a decision tree classification algorithm for remotely sensed satellite data using the separability matrix of the spectral distributions of probable classes in respective bands. The spectral distance between any two classes is calculated from the difference between the minimum spectral value of a class and maximum spectral value of its preceding ...