The application of cross-entropy information processing optimizations to artificial neural network (ANN) training can provide decreased sensitivity to accelerated learning rates as well as insights into the information processing structure of the network. In order to assess the cross-entropy between the desired training goal and the evolving state of network information at each training step, t...

We propose maximizing the change of thermodynamic entropy in order to obtain the probability distributions for nonequilibrium systems in steady or stationary evolution. Arguments are forwarded to support this approach. A path information leading to Kolmogorov-Sinai entropy is defined for an ensemble of possible trajectories between two points in phase space. It is shown that the maximization of...

The price transmission from the international market to the domestic market of tunas was investigated in the present research. For this purpose, the elasticity of substitution between tuna imports with goods produced in Iran (Armington Elasticity) was calculated. Armington elasticity reflects a degree of substitution between commodities produced domestically and those produced abroad. A greater...

The last years have witnessed an increasing attention to entropy-based criteria in adaptive systems. Several principles were proposed based on the maximization or minimization of entropic cost functions. We propose a new type of neural network classifiers with multilayer perceptron (MLP) architecture, but where the usual mean square error minimization principle is substituted by the minimizatio...

In this paper, we focus on the combination of probabilistic logic programming with the principle of maximum entropy. We start by deening probabilistic queries to probabilistic logic programs and their answer substitutions under maximum entropy. We then present an eecient linear programming characterization for the problem of deciding whether a probabilistic logic program is satissable. Finally,...

An amended MaxEnt formulation for systems displaced from the conventional MaxEnt equilibrium is proposed. This formulation involves the minimization of the Kullback-Leibler divergence to a reference Q (or maximization of Shannon Q-entropy), subject to a constraint that implicates a second reference distribution P1 and tunes the new equilibrium. In this setting, the equilibrium distribution is t...

In this paper we discuss the application of some recent results obtained from studying the asymptotics and the entropy of flows in large queueing systems to the analysis of entropy variations of traffic processes in ATM networks. We argue that certain important queueing nodes/networks (e.g. ·/M/1, ·/GI/∞ nodes and Jackson networks) are entropy increasing in nature, in that the entropy of the ar...

In the context of an IP network, this paper investigates an interesting case of the inverse shortest path problem using the concept of network centrality. For a given network, a special probability distribution, namely the centrality distribution associated with the links of a network can be determined based on the number of the shortest paths passing through each link. An entropy measure for t...

We introduce the concept of entropy rate to characterize a diffusion process on a complex network. The entropy rate represents the minimal amount of information necessary to describe the diffusion on the network, and is a quantity extremely sensitive to the network topology and dynamics. By opportunely tuning the kind of diffusion, the entropy rate allows one to extract different properties of ...