Clustering Time Series Gene Expression Data Based on Sum-of-Exponentials Fitting

<p/> <p>This paper presents a method based on fitting a sum-of-exponentials model to the nonuniformly sampled data, for clustering the time series of gene expression data. The structure of the model is estimated by using the minimum description length (MDL) principle for nonlinear regression, in a new form, incorporating a normalized maximum-likelihood (NML) model for a subset of the parameters. The performance of the structure estimation method is studied using simulated data, and the superiority of the new selection criterion over earlier criteria is demonstrated. The accuracy of the nonlinear estimates of the model parameters is analyzed with respect to the Cram&#233;r-Rao lower bounds. Clustering examples of gene expression data sets from a developmental biology application are presented, revealing gene grouping into clusters according to functional classes.</p

2002. Efficient calculation of a physiologically-motivated representation for sound

Abstract: An algorithm is proposed which calculates a computationally efficient approximation of a certain physiologically-motivated representation for sound, called the summary autocorrelation function. This representation has been found very useful in several tasks, such as sound separation, multiple period estimation, and computational auditory scene analysis. However, it has been computationally too complex for most practical applications. The relatively fast algorithm described here proposes only an approximation of the summary autocorrelation function, but the achieved precision is likely to be good enough for most applications. 1

SOME HISTORICAL REMARKS ON SWITCHING THEORY

This paper presents some historical remarks about the development and applications of switching theory, and its central part, the Boolean algebra, in computing and engineering practice

Remarks on History of Abstract Harmonic Analysis

This paper review history of work in the development of abstract harmonic analysis, which is a mathematical discipline attempting to extend the classical Fourier analysis to various groups.

SOME HISTORIC REMARKS ON SAMPLING THEOREM

The sampling theorem is a notion linking continuous and discrete signals. Due to that, it is a very important concept in both engineering practice and mathematical theory, closely related with many other basic results. This paper is a brief review of historic development of the sampling theorem for functions on different groups. 1

Lossy Compression of Noisy Images Based on Visual Quality: A Comprehensive Study

This paper concerns lossy compression of images corrupted by additive noise. The main contribution of the paper is that analysis is carried out from the viewpoint of compressed image visual quality. Several coders for which the compression ratio is controlled in different manner are considered. Visual quality metrics that are the most adequate for the considered application (WSNR, MSSIM, PSNR-HVS-M, and PSNR-HVS) are used. It is demonstrated that under certain conditions visual quality of compressed images can be slightly better than quality of original noisy images due to image filtering through lossy compression. The &#8220;optimal&#8221; parameters of coders for which this positive effect can be observed depend upon standard deviation of the noise. This allows proposing automatic procedure for compressing noisy images in the neighborhood of optimal operation point, that is, when visual quality either improves or degrades insufficiently. Comparison results for a set of grayscale test images and several variances of noise are presented