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Enhancing the performance of neural learning algorithms used in independent component analysis / Abear Mohamed Ezz Eldin Kamel ; Supervised Ibrahim Farag , Amr Goneid

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Abear Mohamed Ezz Eldin Kamel , 2010Description: 168 Leaves : charts ; 30cmOther title:
  • تحسين الأداء لخوارزمات التعلم العصبى المستخدمة فى تحليل المركبات المستقلة [Added title page title]
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Dissertation note: Thesis (Ph.D.) - Cairo University - Faculty of Computers and Information Science - Department of Computer Science Summary: Recently there has been an increasing interest in statistical models for learning data representations. A very popular method for this task is independent component analysis. The ICA methodology was initially proposed to solve the blind source separation (BSS) problem i.e. given only mixtures of a set of underlying sources, the task is to separate the mixed signals and retrieve the original sources
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Item type Current library Home library Call number Copy number Status Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.20.03.Ph.D.2010.Ab.E (Browse shelf(Opens below)) Not for loan 01010110053537000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.20.03.Ph.D.2010.Ab.E (Browse shelf(Opens below)) 53537.CD Not for loan 01020110053537000

Thesis (Ph.D.) - Cairo University - Faculty of Computers and Information Science - Department of Computer Science

Recently there has been an increasing interest in statistical models for learning data representations. A very popular method for this task is independent component analysis. The ICA methodology was initially proposed to solve the blind source separation (BSS) problem i.e. given only mixtures of a set of underlying sources, the task is to separate the mixed signals and retrieve the original sources

Issued also as CD

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