The application of the Maximum Entropy (ME) principle leads to a minimum of the Mutual Information (MI), I(X,Y), between random variables X,Y, which is compatible with prescribed joint expectations and given ME marginal distributions. A sequence of sets of joint constraints leads to a hierarchy of lower MI bounds increasingly approaching the true MI. In particular, using standard bivariate Gaus...

A study was conducted at five villages of Dzongu, North Sikkim in India to identify various constraints faced by the farmers during poultry production. Selection of respondents of poultry farmers was done on the basis of Simple Random Techniques. The data were collected from each respondent through structured questionnaire as well as self observations. The study indicated that the input (82.25%...

an indirect tarns-log production function was employed to estimate the demand functions for such inputs as: fertilizer, seed, pesticide, water recourse and machinery as subject to budget constraint and while using data related to cotton producers in the three provinces of north khorasan, khorasane razavi, and south khorasan in 2007-8. lagrange coefficients with relation to cotton producers in t...

This paper deals with the manufacturing cell formation (MCF) problem, which is based on group technology principles, using a graph partitioning formulation. An attempt has been made to take into account the natural constraints of real-life production systems, such as operation sequences, minimum and maximum numbers of cells, and maximum cell sizes. Cohabitation constraints were added to the pro...

Systems with state and input constraints are prevalent in the practice of control engineering. Most of the research during the past ten years focused on the systems with input constraints. The research activities during this time can broadly be divided into two directions. The first direction follows the so-called a priori design philosophy in which all the constraints are taken into account ri...

The control performance of quadrotor unmanned aerial vehicles (UAVs) in complex environments can be affected by external disturbances and other factors. In this paper, an adaptive neural network backstepping controller based on the barrier Lyapunov function (BLF) is designed for a UAV with internal uncertainties, input–output constraints disturbances. Radial basis networks are used to approxima...