We develop an information-theoretic view of the stochastic block model, a popular statistical model for the large-scale structure of complex networks. A graph G from such a model is generated by first assigning vertex labels at random from a finite alphabet, and then connecting vertices with edge probabilities depending on the labels of the endpoints. In the case of the symmetric two-group mode...

In this paper, visual data analysis was applied to raw medical data using probability theory to provide valuable information for preliminary diagnosis. The evolvable hardware design approach combined with information theory was applied to model an adaptive cardiovascular system. The cardiovascular system is modelled by a digital logic circuit based on ECG and ABP signal samples as input and out...

In this article, we describe an approximate dynamic programming (ADP) approach to compute lower bounds on the optimal value function for a discrete time, continuous space, and infinite horizon setting. The iteratively constructs family of bounding functions by using so-called Bellman inequality. novelty our is that, at each iteration, aim that maximizes point-wise maximum taken with computed th...

We give a sufficient condition on coefficients $a_k$ of an algebraic polynomial $P(z)=\sum\limits_{k=0}^{n}a_kz^k$, $a_n\not=0,$ such that the pointwise Bernstein inequality $|P'(z)|\le n|P(z)|$ is true for all $z,\ |z|\le 1$.

In this paper, we calculate the entanglement-assisted classical information capacity of amplitude damping channel and compare it with the particular mutual information which is considered as the entanglementassisted classical information capacity of this channel in Ref. 6. It is shown that the difference between them is very small. In addition, we point out that using partial symmetry and conca...

This report gives an insight about two major aspects of information theory, including data compression and channel coding. It discusses the simulations results obtained using MATLAB from the information theory view point. It also defines these aspects by using the definitions of entropy and mutual information which reflects the optimum data compression could be obtained and the ultimate transmi...

Quantifying cooperation or synergy among random variables in predicting a single target random variable is an important problem in many complex systems. We review three prior information-theoretic measures of synergy and introduce a novel synergy measure defined as the difference between the whole and the union of its parts. We apply all four measures against a suite of binary circuits to demon...

indeed, we demonstrate that the KGV can also be thought of as We introduce a new contrast function, the kemel mutual information (KMIj, to measure the degree of independence of continuous random variables. This contrast function provides an approximate upper bound on the mutual information, as measured near independence, and is based on a kernel density estimate of the mutual information betwee...

Characterization of the correlations of a multiparticle system remains an open problem. We generalize the notion of quantum discord, using multivariate mutual information, to characterize the quantum properties of a multiparticle system. This new measure, called dissension, is a set of numbers – quantumness vector. There are a number of different possible generalizations. We consider two of the...