Temat: neural scheme - Prolib Integro

Skocz do pozycji: 1.

Tytuł:: To recognize the manuscript texts of Arabic letters in ancient Uzbek script
Autorzy:: Nurmamatovna, Iskandarova Sayyora
Tematy:: Arabic text
Hemming
biologic neural
method
neural model
neural scheme
recognize
software product; Pokaż więcej
Wydawca:: Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Powiązania:: https://bibliotekanauki.pl/articles/1076553.pdf Link otwiera się w nowym oknie
Opis:: This article describes the Hemming method of the neural model for automatic identification of Arabic texts on the computer. The main problem of recognizing manuscript mantles in Arabic is that of the elements that they have created. Usually, the text is divided into rows, and then separated by separate words. The development of the Arabic language signifies a great deal of controversy over Arabic language. Hemming is based on the neuronal model and the description of the software product.
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Overcoming Localization Errors due to Node Power Drooping in a Wireless Sensor Network
Autorzy:: Khan, S. A.
Daachi, B.
Djouani, K.
Tematy:: wireless sensor networks
RSSI
localization
range-free scheme
energy considerations
neural networks; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/226280.pdf Link otwiera się w nowym oknie
Opis:: Received Signal Strength Indication (RSSI) plays a vital role in the range-free localization of sensor nodes in a wireless sensor network and a good amount of research has been made in this regard. One important factor is the battery voltage of the nodes (i.e., the MICAz sensors) which is not taken into account in the existing literature. As battery voltage level performs an indispensable role for the position estimation of sensor nodes through anchor nodes therefore, in this paper, we take into a account this crucial factor and propose an algorithm that overcomes the problem of decaying battery. We show the results, in terms of more precise localization of sensor nodes through simulation. This work is an extension to [1] and now we also use neural network to overcome the localization errors generated due to gradual battery voltage drooping.
Dostawca treści:: Biblioteka Nauki

Artykuł

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