In actual application, sensors are prone to failure because of harsh environments, battery drain, and sensor aging. Sensor fault location is an important step for follow-up sensor fault detection. In this paper, two new multi-level wavelet Shannon entropies (multi-level wavelet time Shannon entropy and multi-level wavelet time-energy Shannon entropy) are defined. They take full advantage of sen...

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...

We study the correlation of the ground state of an N-particle Moshinsky model by computing the Shannon entropy in both position and momentum spaces. We have derived the Shannon entropy and mutual information with analytical forms of such an N-particle Moshinsky model, and this helps us test the entropic uncertainty principle. The Shannon entropy in position space decreases as interaction streng...

Shannon wavelets are studied together with their differential properties known as connection coefficients . It is shown that the Shannon sampling theorem can be considered in a more general approach suitable for analyzing functions ranging in multifrequency bands. This generalization coincides with the Shannon wavelet reconstruction of L2 R functions. The differential properties of Shannon wave...

1 Justification Shannon is a synchronous stream cipher with message authentication functionality, designed according to the ECrypt NoE call for stream cipher primitives, profile 1A (but well after the call). Shannon is named in memory of Claude E. Shannon[20] of Bell Labs and MIT, founder of Information Theory. Shannon is an entirely new design, influenced by members of the SOBER family of stre...

We provide a new inequality that links two important entropy notions: Shannon Entropy H1 and collision entropy H2. Our formula gives the worst possible amount of collision entropy in a probability distribution, when its Shannon Entropy is fixed. While in practice it is easier to evaluate Shannon entropy than other entropy notions, it is well known in folklore that it does not provide a good est...