This paper uses the Maximum Entropy Principle to construct a 1-K-1 constrained sigmoidal neural network which adaptively adjusts its gain parameters to control the transfer function in order to maximize the entropy measure at the output for image contrast enhancement. We demonstrate how the model works with the standard lena image.

In social networks, it is conventionally thought that two individuals with more overlapped friends tend to establish a new friendship, which could be stated as homophily breeding new connections. While the recent hypothesis of maximum information entropy is presented as the possible origin of effective navigation in small-world networks. We find there exists a competition between information en...

Space plasmas are frequently described by kappa distributions. Non-extensive statistical mechanics involves the maximization of the Tsallis entropic form under the constraints of canonical ensemble, considering also a dyadic formalism between the ordinary and escort probability distributions. This paper addresses the statistical origin of kappa distributions, and shows that they can be connecte...

A likelihood maximization approach to image registration is developed in this paper. It is assumed that the voxel values in two images in registration are probabilistically related. The principle of maximum likelihood is then exploited to find the optimal registration: the likelihood that given image f, one has image g and given image g, one has image f is optimized with respect to registration...

We consider the general problem of relative entropy minimization and entropy maximization subject to expectation constraints. We show that the solutions can be represented as members of an exponential family subject to weaker conditions than previously shown, and the representation can be simplified further if an appropriate conjugate prior density is used. As a result, the solutions can be fou...

Let X1; : : : ;Xn be n independent, symmetric random variables supported on the interval [-1,1] and let Sn = Pn i=1Xi be their sum. We show that the di erential entropy of Sn is maximized when X1; : : : ;Xn 1 are Bernoulli taking on +1 or -1 with equal probability and Xn is uniformly distributed. This entropy maximization problem is due to Shlomo Shamai [1] who also conjectured the solution1.

The problem of image object extraction in the framework of rough sets and granular computing is addressed. A measure called ‘‘rough entropy of image’’ is defined based on the concept of image granules. Its maximization results in minimization of roughness in both object and background regions; thereby determining the threshold of partitioning. Methods of selecting the appropriate granule size a...

A general theory for the stability and coexistence of nonequilibrium phases is formulated. An integral formulation of the second entropy is given, the functional maximization of which yields nonlinear hydrodynamics. Rayleigh-Bénard convection is analyzed, and analytic approximations are obtained for the second entropy for conduction and for convection. Despite the simplicity of the model, coexi...

It is shown that in a stressed granular packing, the effect of the applied pressure and structural randomness on the contact force distribution can be described accurately by a variational principle of minimizing energy subject to the constraint of keeping entropy at a fixed value. The constraint on entropy may be regarded as a measure of the degree of retained disorderness in the system. This ...