نتایج جستجو برای: nn implementation
تعداد نتایج: 372770 فیلتر نتایج به سال:
Neural Networks (NN) hold the potential for improving a variety of tasks in remote sensing and image processing. They represent a different approach to problems, as they do not rely on statistical relationships. Instead, neural networks adaptively estimate continuous functions from data without specifying mathematically how outputs depend on inputs. This paper evaluates the effect of metrics se...
Hybrid-Layers Neural Network Architectures for Modeling the Self-Interference in Full-Duplex Systems
Full-duplex (FD) systems have been introduced to provide high data rates for beyond fifth-generation wireless networks through simultaneous transmission of information over the same frequency resources. However, operation FD is practically limited by self-interference (SI), and efficient SI cancelers are sought make realizable. Typically, polynomial-based employed mitigate SI; nevertheless, the...
This paper presents a novel Nearest Neighbor (NN) classifier. NN classification is a well studied method for pattern classification having the following properties; * it performs maximum-margin classification and achieves less than the twice of ideal Bayesian error, * it does not require the knowledge on pattern distributions, kernel functions or base classifiers, and * it can naturally be appl...
روابط کمی ساختارـفعالیت یا ویژگی (qsar/qspr) یکی از فنون نویدبخش در زمینه روش های مجازی به منظور پیش بینی ویژگی های شیمیایی است. این روش ها، با استفاده از توصیف کننده هایی که از ساختار مولکولی منتج می شوند، به جستجوی الگویی در داده ها می پردازند تا فعالیت یا ویژگی مواد شیمیایی جدیدی را که ویژگیهای مولکولی مشابهی دارند، پیش بینی کنند. در بخش اول این پروژه، از روش qspr، جهت پیش بینی پتانسیل اکسا...
Inclusive jet production in pPb collisions at a nucleon–nucleon (NN) center-of-mass energy of √ s NN = 5.02 TeV is studied with the CMS detector at the LHC. A data sample corresponding to an integrated luminosity of 30.1 nb −1 is analyzed. The jet transverse momentum spectra are studied in seven pseudorapidity intervals covering the range −2.0 < η CM < 1.5 in the NN center-of-mass frame. The je...
In this paper we propose, describe, and evaluate a novel deep learning method for classifying binary motor imagery data. This model is designed to perform CSP-like feature extractions. It can be seen as a neural network with a specifically designed architecture where the latent space corresponds naturally to the features found in CSP methods. Our model allows for easy generalization from spatia...
Text categorization refers to the task of assigning the pre-defined classes to text documents based on their content. k-NN algorithm is one of top performing classifiers on text data. However, there is little research work on the use of different voting methods over text data. Also, when a huge number of training data is available online, the response speed slows down, since a test document has...
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