We introduce the Redundant Information Neural Estimator (RINE), a method that allows efficient estimation for component of information about target variable is common to set sources, known as “redundant information”. show existing definitions redundant can be recast in terms an optimization over family functions. In contrast previous decompositions, which only evaluated discrete variables small...

in this paper for calculating policy analysis matrix parameters, with regard to real or shadow prices, we pay attention to variation of endogenous variables, using results of cge  model. the results of the study indicated that,in output market, because of government policies, there are implicit tax on products of iran;s auto industry. but inputs of auto industry, benefits from government subsid...

Deploying the new generation ”Internet Protocol” (IPv6) over 802.16-based wireless networks is facing an important challenge as the IEEE 802.16 standard is failing to support IPv6 functionalities. In fact, unlike the other 802 standards, the IEEE 802.16 is based on a point-tomultipoint (PMP) communication model, where no direct connection (at the MAC layer) is possible between two stations, all...

In this study, we describe an auto-calibration algorithm with fixed but unknown camera parameters. We have modified Triggs’ algorithm to incorporate known aspect ratio and skew values to make it applicable for small rotation around a single axis. The algorithm despite being a quadratic one is easy to solve. We have applied the algorithm to some artificial objects with known size and dimensions ...

_ By D. N. SEN, l-m.s., Pathologist, Sambhunath Pandit Hospital, Alipore? Note by Major GOURLAY, d-s.o-, Surgeon Supdt., Sambhunath Pandit Hospital. In introducing this paper by Dr. D. N. Sen, Pathologist of the Sambhunath Pandit Hospital. I must admit that I have no first-hand acquaintance with the literature of auto-haemic therapy. At the same time, the subject appears to be an extraordinaril...

Binary codes can be used to speed up nearest neighbor search tasks in large scale data sets as they are efficient for both storage and retrieval. In this paper, we propose a robust auto-encoder model that preserves the geometric relationships of high-dimensional data sets in Hamming space. This is done by considering a noise-removing function in a region surrounding the manifold where the train...

Auto-encoder is a special kind of neural network based on reconstruction. De-noising auto-encoder (DAE) is an improved auto-encoder which is robust to the input by corrupting the original data first and then reconstructing the original input by minimizing the reconstruction error function. And contractive auto-encoder (CAE) is another kind of improved auto-encoder to learn robust feature by int...