Detection of code-division multiple access signals based on neural network

المؤلف

al-Shaban, Sad

المصدر

Iraqi Journal of Computer, Communications and Control Engineering

العدد

المجلد 5، العدد 1 (30 يونيو/حزيران 2005)، ص ص. 88-93، 6ص.

الناشر

الجامعة التكنولوجية

تاريخ النشر

2005-06-30

دولة النشر

العراق

عدد الصفحات

6

التخصصات الرئيسية

تكنولوجيا المعلومات وعلم الحاسوب

الملخص EN

Artificial Neural Networks are employed for demodulation of spread spectrum signals in a multiple-access environment.

In fact, the conventional matched filter receiver, when used in multi-user system, suffers from the interfering signals, so that when reducing this problem, we need to make the receiver in optimum state.

This receiver is too complex for practical use.

Two simple structures employing multilayer nodes are produced for demodulation of spread-spectrum signals.

The Neural Networks are trained for the demodulation of signals by using back propagation type algorithms.

A comparative analysis of the two receivers, the conventional and that employing Neural Network, has been presented.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

al-Shaban, Sad. 2005. Detection of code-division multiple access signals based on neural network. Iraqi Journal of Computer, Communications and Control Engineering،Vol. 5, no. 1, pp.88-93.
https://search.emarefa.net/detail/BIM-361555

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

al-Shaban, Sad. Detection of code-division multiple access signals based on neural network. Iraqi Journal of Computer, Communications and Control Engineering Vol. 5, no. 1 (2005), pp.88-93.
https://search.emarefa.net/detail/BIM-361555

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

al-Shaban, Sad. Detection of code-division multiple access signals based on neural network. Iraqi Journal of Computer, Communications and Control Engineering. 2005. Vol. 5, no. 1, pp.88-93.
https://search.emarefa.net/detail/BIM-361555

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references : p. 92-93

رقم السجل

BIM-361555