This paper is concerned with the problem of design and implementation a robust adaptive control strategy for flexible joint electrically driven robots (FJEDR), while considering to the constraints on the actuator voltage input. The control design procedure is based on function approximation technique, to avoid saturation besides being robust against both structured and unstructured uncertaintie...

designing wireless sensor networks should meet appropriate parameters such as quality of service (qos) defined by different users. the variable physical conditions of the environment, processing and transmission power limitations and limited communication capabilities are the most important obstacles that influence qos parameters such as throughput, delay, reliability and network lifetime. the ...

In this paper, we propose a novel adaptive reducedrank decision feedback (DF) receiver strategy based on the minimization symbol-error-rate (MSER) criterion for largescale multiple-antenna systems. In this strategy, a reduced-rank method for general parameter estimation using an adaptive joint and iterative preprocessing, decimation and filtering (JPDF) scheme is proposed for DF receive process...

With the rapid development of computer technology information theory has been implemented for searching optimal adaptive item sequence in computerised adaptive test systems based on Bayesian network. Information theory such as entropy between dichotomous concepts and test items generalise common intuitions about item comparison for heuristic methodology. However, the executive time and the stor...

Adaptive learning can transform the way students learn. Because tailored content and teaching resources strive to understand what a student knows, and how he or she is approaching the task at hand, they can personalize the learning experience. However, unless an organization has a clear implementation strategy, adaptive learning can become a complex and expensive endeavor. So, how can publisher...

Here, issues connected with characteristic stochastic practices are considered. In the first part, the plausibility of covering the arrangements of an improvement issue on subjective subgraphs is studied. The impulse for this strategy is a state where an advancement issue must be settled as often as possible for discretionary illustrations. Then, a preprocessing stage is considered that would q...

A genetic recombination framework is presented within which both the unit of inheritance of genetic material from a parent, and the number of parents involved in the creation of a new individual are potentially learnt through the evolution of competing subpopulations representing different strategies. At the heart of the framework is a recombination mechanism whereby a newly created member of t...

We consider the problem of stratified sampling for Monte Carlo integration of a random variable. We model this problem in a K-armed bandit, where the arms represent the K strata. The goal is to estimate the integral mean, that is a weighted average of the mean values of the arms. The learner is allowed to sample the variable n times, but it can decide on-line which stratum to sample next. We pr...

Anti-idiotype of (natural) autoantibodies participate in the regulation of autoantibodies, their idiotypes. Focusing on an idiotype/anti-idiotype pair embedded in an environment such as the central immune system, we start with the experimental fact that the level of anti-idiotypes is low in autoimmune patients but high in healthy individuals, and present a quantitative model. This is then used ...

In this paper a new hp-adaptive strategy for elliptic problems based on refinement history is proposed, which chooses h-, por hp-refinement on individual elements according to a posteriori error estimate, as well as smoothness estimate of the solution obtained by comparing the actual and expected error reduction rate. Numerical experiments show that exponential convergence can be achieved with ...