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Article
Blind Detection Method of MIMO – Space Time Coded Wireless Systems Based on ICA
طريقة الكشف الأعمى لأنظمة الترميز الزمنية- متعددة المداخل متعددة المخارج اللاسلكية بالاعتماد على التحليل المستقل للعناصر

Author: Wafaa Mohammed R. Shakir AL-Dahan
Journal: Engineering and Technology Journal مجلة الهندسة والتكنولوجيا ISSN: 16816900 24120758 Year: 2014 Volume: 32 Issue: 4 Part (A) Engineering Pages: 842-854
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

This paper presents a proposed blind detection method for Multiple Input Multiple Output-Space Time Coded (MIMO-STC) wireless systems based on Independent Component Analysis (ICA). The proposed method used the statistical independence of the sources of signals for blindly detection of STC signals. The original transmitted signals are estimated by gradient the kurtosis-based objective function of the received signals. In contrast to other approaches, the proposed method does not require any modification in transmission side or using the training sequences. Simulation results using MATLAB demonstrate competitive results for the proposed system comparing with conventional Minimum Mean Squared Error (MMSE) detector. Where at (10-7) Bit Error Rate (BER) there is about (4 dB) and (7.5 dB) improvement in Signal to Noise Ratio (SNR) for the proposed system adopting Orthogonal Space-Time Block Coded (OSTBC) scheme with (6) receiving antennae comparing to the same system with (4) and (2) receiving antennae respectively.

في هذا البحث يتم تقديم طريقة استقبال عمياء لإشارات أنظمة الترميز الزمني متعدد المداخل متعدد المخارج بالاعتماد على طريقة التحليل المستقل للعناصر. يستغل المستلم المبني حسب على الطريقة المقترحة البناء الإحصائي لمصادر الإشارات المستلمة لغرض كشف الإشارات اللاسلكية لأنظمة الترميز بصورة عمياء. يتم تخمين الإشارات المرسلة باستخدام طريقة انحدار المعادلة الموضوعية للإشارات المستلمة. يتميز الأسلوب المقترح بأنه لا يتطلب أي تعديل لجهاز الإرسال أو إرسال إشارات التدريب. وتوضح المحاكاة المبرمجة بواسطة الماتلاب نتائج أداء تنافسية للطريقة المقترحة مقارنة مع نتائج أداء كاشف (MMSE) التقليدي. حيث يحقق المستلم المقترح ذو(6) هوائيات استلام وطريقة الترميز (OSTBC) ربح بحدود (4 dB) و (7.5 dB) مقارنة مع نفس المستلم لكن بعدد هوائيات استلام (4) و(2) على التوالي عند(BER=10-7) .


Article
A study the effect of trigger circuit on flash lamp life
إلغاء التداخل الأعمى للأنظمة متعددة المداخل متعددة المخارج اللاسلكية بالاعتماد على خوارزمية التحليل المستقل للعناصر

Authors: Wafaa Mohammed R --- Shakir AL-Dahan
Journal: journal of kerbala university مجلة جامعة كربلاء ISSN: 18130410 Year: 2013 Volume: 11 Issue: 3 Pages: 173-183
Publisher: Kerbala University جامعة كربلاء

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Abstract

In this paper, a new method for blind interference cancellation of Multiple Input Multiple Output (MIMO) wireless communication systems based on Independent Component Analysis (ICA) is proposed. A proposed ICA algorithm exploits the Higher Order Statistical (HOS) of the observation signals for blindly interference cancellation and signals estimation processes is presented. In contrast to other methods, the proposed method does not require any modification in transmission side or using the training sequences that usually costs a bandwidth. Simulation results show the ability of the proposed algorithm to cancel the interference effects of the multipath fading channel comparing with other ICA algorithms and conventional method.

في هذا البحث يتم تقديم طريقة جديدة لإلغاء تداخل الإشارات اللاسلكية للأنظمة متعددة المداخل متعددة المخارج اللاسلكية بالاعتماد على خوارزمية التحليل المستقل للعناصر بصورة عمياء. يتم استخدام خوارزمية مقترحة للتحليل المستقل للعناصر تعتمد على البناء الإحصائي لمصادر الإشارات المرسلة لغرض تخمين وإلغاء تأثير التداخل الناتج من قناة الانتشار اللاسلكية متعددة المسارات على الإشارة المستلمة. تتميز الطريقة المقترحة بأنها لا تتطلب أي تعديل لجهاز الإرسال أو إرسال إشارات التدريب التي تقلل من عرض النطاق الترددي. وتوضح نتائج المحاكاة فوائد الخوارزمية المقترحة مقارنة مع أساليب تقليدية أخرى ومقارنة مع خوارزميات التحليل المستقل للعناصر الأخرى.


Article
Session to Session Transfer Learning Method Using Independent Component Analysis with Regularized Common Spatial Patterns for EEG-MI Signals

Authors: Zaineb M. Alhakeem --- Ramzy S. Ali
Journal: Iraqi Journal for Electrical And Electronic Engineering المجلة العراقية للهندسة الكهربائية والالكترونية ISSN: 18145892 Year: 2019 Volume: 15 Issue: 1 Pages: 13-27
Publisher: Basrah University جامعة البصرة

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Abstract

Training the user in Brain-Computer Interface (BCI) systems based on brain signals that recorded usingElectroencephalography Motor Imagery (EEG-MI) signal is a time-consuming process and causes tiredness to thetrained subject, so transfer learning (subject to subject or session to session) is very useful methods of training that willdecrease the number of recorded training trials for the target subject. To record the brain signals, channels orelectrodes are used. Increasing channels could increase the classification accuracy but this solution costs a lot of moneyand there are no guarantees of high classification accuracy. This paper introduces a transfer learning method usingonly two channels and a few training trials for both feature extraction and classifier training. Our results show that theproposed method Independent Component Analysis with Regularized Common Spatial Pattern (ICA-RCSP) willproduce about 70% accuracy for the session to session transfer learning using few training trails. When the proposedmethod used for transfer subject to subject the accuracy was lower than that for session to session but it still better thanother methods.


Article
Independent Component Analysis for Separation of Speech Mixtures: A Comparison Among Thirty Algorithms

Author: Ali Al-Saegh
Journal: Iraqi Journal for Electrical And Electronic Engineering المجلة العراقية للهندسة الكهربائية والالكترونية ISSN: 18145892 Year: 2015 Volume: 11 Issue: 1 Pages: 1-9
Publisher: Basrah University جامعة البصرة

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Abstract

Vast number of researches deliberated the separation of speech mixtures due to the importance of this fieldof research. Whereas its applications became widely used in our daily life; such as mobile conversation, videoconferences, and other distant communications. These sorts of applications may suffer from what is well known thecocktail party problem. Independent component analysis (ICA) has been extensively used to overcome this problem andmany ICA algorithms based on different techniques have been developed in this context. Still coming up with somesuitable algorithms to separate speech mixed signals into their original ones is of great importance. Hence, this paperutilizes thirty ICA algorithms for estimating the original speech signals from mixed ones, the estimation process iscarried out with the purpose of testing the robustness of the algorithms once against a different number of mixed signalsand another against different lengths of mixed signals. Three criteria namely Spearman correlation coefficient, signalto interference ratio, and computational demand have been used for comparing the obtained results. The results of thecomparison were sufficient to signify some algorithms which are appropriate for the separation of speech mixtures.


Article
High Rate Data Processing System of 6x6 MIMO_OFDM Using FPGA Technique with Spatial Algorithm

Author: Muthna J. Fadhil
Journal: Engineering and Technology Journal مجلة الهندسة والتكنولوجيا ISSN: 16816900 24120758 Year: 2018 Volume: 36 Issue: 7 Part (A) Engineering Pages: 723-732
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

OFDM has high spectral Performance and pliability in multipath channel effects while MIMO use another strategy for saving power of transmitter by using multi in multi out antennas to make throughput processing in high efficiency. The transceiver MIMO OFDM implemented on an FPGA typeSpartan3 XC3S200 with proper algorithm, Invoke method and QPSK modulation. The project prospective to improve the transceiver operations in terms of data transmission in high speed and saving power for wireless communication system take in consideration the cost of implementation hardware. In the result registered throughput data rate 425 Mbps using spatial algorithm (ICA with SD algorithm) with another advantage reduction in PAR by 6db and BER less than 10-7).The total architecture using 61% slice registers, LUT's of 55% and memory about 67% on board of Spartan-3 XC3S200.


Article
Comparison of Complex-Valued Independent Component Analysis Algorithms for EEG Data

Author: Ali Al-Saegh
Journal: Iraqi Journal for Electrical And Electronic Engineering المجلة العراقية للهندسة الكهربائية والالكترونية ISSN: 18145892 Year: 2019 Volume: 15 Issue: 1 Pages: 1-12
Publisher: Basrah University جامعة البصرة

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Abstract

Independent Component Analysis (ICA) has been successfully applied to a variety of problems, fromspeaker identification and image processing to functional magnetic resonance imaging (fMRI) of the brain. Inparticular, it has been applied to analyze EEG data in order to estimate the sources form the measurements.However, it soon became clear that for EEG signals the solutions found by ICA often depends on the particular ICAalgorithm, and that the solutions may not always have a physiologically plausible interpretation. Therefore, nowadaysmany researchers are using ICA largely for artifact detection and removal from EEG, but not for the actual analysis ofsignals from cortical sources. However, a recent modification of an ICA algorithm has been applied successfully toEEG signals from the resting state. The key idea was to perform a particular preprocessing and then apply a complexvaluedICA algorithm.In this paper, we consider multiple complex-valued ICA algorithms and compare their performance on real-worldresting state EEG data. Such a comparison is problematic because the way of mixing the original sources (the “groundtruth”) is not known. We address this by developing proper measures to compare the results from multiple algorithms.The comparisons consider the ability of an algorithm to find interesting independent sources, i.e. those related to brainactivity and not to artifact activity. The performance of locating a dipole for each separated independent component isconsidered in the comparison as well.Our results suggest that when using complex-valued ICA algorithms on preprocessed signals the resting state EEGactivity can be analyzed in terms of physiological properties. This reestablishes the suitability of ICA for EEG analysisbeyond the detection and removal of artifacts with real-valued ICA applied to the signals in the time-domain.


Article
Blind MIMO Channel Estimation of CDMA System

Author: Wafaa Mohammed R. Shakir AL-Dahan.
Journal: Journal of University of Babylon مجلة جامعة بابل ISSN: 19920652 23128135 Year: 2014 Volume: 22 Issue: 9 Pages: 2255-2265
Publisher: Babylon University جامعة بابل

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Abstract

In this paper, a blind receiving system for Multiple Input Multiple Output (MIMO) channel estimation of Code Division Multiple Access (CDMA) system based on Independent Component Analysis (ICA) is proposed. The proposed receiving system exploits the statistical independence of the received signals in order to blind wireless channel estimation processes. The MIMO channel matrix is estimated by gradient kurtosis-based objective function of the received signals. In contrast to other approaches, the proposed method does not require any modification in the transmission side or using the training signals. Simulation results demonstrate the benefits of the proposed method comparing with other conventional methods.

في هذا البحث يتم تقديم نظام استقبال أعمى لإشارات نظام تعدد الوصولية بتقسيم الشفرة متعددة المداخل متعددة المخارج بالاعتماد على طريقة التحليل المستقل للعناصر. يستغل نظام الاستقبال المقترح البناء الإحصائي لمصادر الإشارات المستلمة لغرض تخمين وإلغاء تأثير قناة الانتشار اللاسلكية على الإشارة المستلمة. يتم تخمين تأثير قناة الانتشار باستخدام طريقة انحدار المعادلة الموضوعية للإشارات المستلمة. يتميز الأسلوب المقترح بأنه لا يتطلب أي تعديل لجهاز الإرسال أو إرسال إشارات التدريب. وتوضح نتائج المحاكاة فوائد الطريقة المقترحة مقارنة مع أساليب تقليدية أخرى.

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