Image Segmentation plays an important role in medical field that enable professionals to detect their patient’s problems and help them to get proper diagnosed. In this article, an entropy based approach for image segmentation is discussed to highlight tumor in MRI images. Magnetic Resonance Imaging (MRI) is an imaging, in which pixel values are based on radiation absorption. In the proposed app...

A new set of time-dependent deterministic sampling (TDDS) measures, based on local Shannon entropy, are presented to adaptively gauge the importance of various regions on a potential energy surface and to be employed in "on-the-fly" quantum dynamics. Shannon sampling and Shannon entropy are known constructs that have been used to analyze the information content in functions: for example, time-s...

a review of damages caused by landslide shows the need for studying effective parameters in landslide occurrence and prediction. this study aims to improve landslide prediction results for tutkabon region in gilan province. to this end, shannon entropy theory was employed for modeling and considering data uncertainty. slope, height, geomorphologic conditions, earth’s curve, closeness to river, ...

Traditional detectors for spectrum sensing in cognitive radio networks always become disabled when noise uncertainty is severe. Shannon entropy-based detection methods have aroused widespread attention in recent years due to the characteristics of effective anti-noise uncertainty. However, in existing entropy-based sensing schemes, the uniform quantization method cannot guarantee the maximum en...

In this paper, we show that in order to obtain the Tsallis entropy rate for stochastic processes, we can use the limit of conditional entropy, as it was done for the case of Shannon and Renyi entropy rates. Using that we can obtain Tsallis entropy rate for stationary Gaussian processes. Finally, we derive the relation between Renyi, Shannon and Tsallis entropy rates for stationary Gaussian proc...

The concept of Shannon entropy as a measure of disorder is introduced and the generalisations of the Rényi and Tsallis entropy are motivated and defined. A number of different estimators for Shannon, Rényi and Tsallis entropy are defined in the theoretical part and compared by simulation in the practical part. In this work the nearest neighbour estimator presented in Leonenko and Pronzato (2010...

This manual describes the Fortran 90 implementation of maximum-entropy basis functions. The main ingredients of the theory are presented, and then the numerical implementation is touched upon. Instructions on the installation and execution of the code, as well as on writing an interface to the library are presented. Each program module and the most important functions in each module are discuss...

The global maximum of an entropy function with different decision levels for a three-level scalar quantizer performed after a discrete wavelet transform was derived. Herein, we considered the case of entropy-constrained scalar quantization capable of avoiding many compression ratio reductions as the mean squared error was minimized. We also dealt with the problem of minimum entropy with an erro...