Problem of Сonstructing the GMDH Neural Networks with Active Neurons

Inductive sorting-out GMDH algorithms with polynomial complexity for active neurons of neural network

Neural networks with active neurons which selforganize their structure can use inductive sorting-out GMDH algorithms for their neurons. New threshold type GMDH algorithm with polynomial complexity is developed to decrease computing time in case of large input data sample.

the problem of divine hiddenness

این رساله به مساله احتجاب الهی و مشکلات برهان مبتنی بر این مساله میپردازد. مساله احتجاب الهی مساله ای به قدمت ادیان است که به طور خاصی در مورد ادیان ابراهیمی اهمیت پیدا میکند. در ادیان ابراهیمی با توجه به تعالی خداوند و در عین حال خالقیت و حضور او و سخن گفتن و ارتباط شهودی او با بعضی از انسانهای ساکن زمین مساله ای پدید میاید با پرسشهایی از قبیل اینکه چرا ارتباط مستقیم ویا حداقل ارتباط وافی به ب...

The effects of supraphysiological levels of testosterone on neural networks upstream of gonadotropin-releasing hormone neurons

Objective(s): Several pathological conditions are associated with hyper-production of testosterone; however, its impacts are not well understood. Hence, we evaluated the effects of supraphysiological levels of testosterone on gonadotropin-releasing hormone (GnRH) system in the hypothalamus of male rats. Also, we assessed the expression of two excitatory (kisspeptin and...

GMDH Type Neural Networks and Their Application to the Identification of the Inverse Kinematics Equations of Robotic Manipulators (RESEARCH NOTE)

Active Learning with Neural Networks

This paper is a survey over the area of active learning algorithms for supervised Neural Networks. These algorithms are concerned with the selection of informative examples to be included into the training set used for learning. After an introduction into the field and the motives for its development, three practical algorithms will be introduced. These are a network function inversion algorith...