Search results for: Blind equalization
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 167

Search results for: Blind equalization

107 Antenna Array Beamforming Using Neural Network

Authors: Maja Sarevska, Abdel-Badeeh M. Salem

Abstract:

This paper considers the problem of Null-Steering beamforming using Neural Network (NN) approach for antenna array system. Two cases are presented. First, unlike the other authors, the estimated Direction Of Arrivals (DOAs) are used for antenna array weights NN-based determination and the imprecise DOAs estimations are taken into account. Second, the blind null-steering beamforming is presented. In this case the antenna array outputs are presented at the input of the NN without DOAs estimation. The results of computer simulations will show much better relative mean error performances of the first NN approach compared to the NNbased blind beamforming.

Keywords: Beamforming, DOAs, neural network.

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106 Floating-Point Scaling for BSS Gain Control

Authors: Abdelmalek Fermas, Adel Belouchrani, Otmane Ait Mohamed

Abstract:

In Blind Source Separation (BSS) processing, taking advantage of scaling factor indetermination and based on the floatingpoint representation, we propose a scaling technique applied to the separation matrix, to avoid the saturation or the weakness in the recovered source signals. This technique performs an Automatic Gain Control (AGC) in an on-line BSS environment. We demonstrate the effectiveness of this technique by using the implementation of a division free BSS algorithm with two input, two output. This technique is computationally cheaper and efficient for a hardware implementation.

Keywords: Automatic Gain Control, Blind Source Separation, Floating-Point Representation, FPGA Implementation.

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105 A Mixing Matrix Estimation Algorithm for Speech Signals under the Under-Determined Blind Source Separation Model

Authors: Jing Wu, Wei Lv, Yibing Li, Yuanfan You

Abstract:

The separation of speech signals has become a research hotspot in the field of signal processing in recent years. It has many applications and influences in teleconferencing, hearing aids, speech recognition of machines and so on. The sounds received are usually noisy. The issue of identifying the sounds of interest and obtaining clear sounds in such an environment becomes a problem worth exploring, that is, the problem of blind source separation. This paper focuses on the under-determined blind source separation (UBSS). Sparse component analysis is generally used for the problem of under-determined blind source separation. The method is mainly divided into two parts. Firstly, the clustering algorithm is used to estimate the mixing matrix according to the observed signals. Then the signal is separated based on the known mixing matrix. In this paper, the problem of mixing matrix estimation is studied. This paper proposes an improved algorithm to estimate the mixing matrix for speech signals in the UBSS model. The traditional potential algorithm is not accurate for the mixing matrix estimation, especially for low signal-to noise ratio (SNR).In response to this problem, this paper considers the idea of an improved potential function method to estimate the mixing matrix. The algorithm not only avoids the inuence of insufficient prior information in traditional clustering algorithm, but also improves the estimation accuracy of mixing matrix. This paper takes the mixing of four speech signals into two channels as an example. The results of simulations show that the approach in this paper not only improves the accuracy of estimation, but also applies to any mixing matrix.

Keywords: Clustering algorithm, potential function, speech signal, the UBSS model.

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104 A Robust Hybrid Blind Digital Image Watermarking System Using Discrete Wavelet Transform and Contourlet Transform

Authors: Nidal F. Shilbayeh, Belal AbuHaija, Zainab N. Al-Qudsy

Abstract:

In this paper, a hybrid blind digital watermarking system using Discrete Wavelet Transform (DWT) and Contourlet Transform (CT) has been implemented and tested. The implemented combined digital watermarking system has been tested against five common types of image attacks. The performance evaluation shows improved results in terms of imperceptibility, robustness, and high tolerance against these attacks; accordingly, the system is very effective and applicable.

Keywords: DWT, contourlet transform, digital image watermarking, copyright protection, geometric attack.

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103 Blind Channel Estimation Based on URV Decomposition Technique for Uplink of MC-CDMA

Authors: Pradya Pornnimitkul, Suwich Kunaruttanapruk, Bamrung Tau Sieskul, Somchai Jitapunkul

Abstract:

In this paper, we investigate a blind channel estimation method for Multi-carrier CDMA systems that use a subspace decomposition technique. This technique exploits the orthogonality property between the noise subspace and the received user codes to obtain channel of each user. In the past we used Singular Value Decomposition (SVD) technique but SVD have most computational complexity so in this paper use a new algorithm called URV Decomposition, which serve as an intermediary between the QR decomposition and SVD, replaced in SVD technique to track the noise space of the received data. Because of the URV decomposition has almost the same estimation performance as the SVD, but has less computational complexity.

Keywords: Channel estimation, MC-CDMA, SVD, URV.

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102 An ICA Algorithm for Separation of Convolutive Mixture of Speech Signals

Authors: Rajkishore Prasad, Hiroshi Saruwatari, Kiyohiro Shikano

Abstract:

This paper describes Independent Component Analysis (ICA) based fixed-point algorithm for the blind separation of the convolutive mixture of speech, picked-up by a linear microphone array. The proposed algorithm extracts independent sources by non- Gaussianizing the Time-Frequency Series of Speech (TFSS) in a deflationary way. The degree of non-Gaussianization is measured by negentropy. The relative performances of algorithm under random initialization and Null beamformer (NBF) based initialization are studied. It has been found that an NBF based initial value gives speedy convergence as well as better separation performance

Keywords: Blind signal separation, independent component analysis, negentropy, convolutive mixture.

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101 Blind Identification of MA Models Using Cumulants

Authors: Mohamed Boulouird, Moha M'Rabet Hassani

Abstract:

In this paper, many techniques for blind identification of moving average (MA) process are presented. These methods utilize third- and fourth-order cumulants of the noisy observations of the system output. The system is driven by an independent and identically distributed (i.i.d) non-Gaussian sequence that is not observed. Two nonlinear optimization algorithms, namely the Gradient Descent and the Gauss-Newton algorithms are exposed. An algorithm based on the joint-diagonalization of the fourth-order cumulant matrices (FOSI) is also considered, as well as an improved version of the classical C(q, 0, k) algorithm based on the choice of the Best 1-D Slice of fourth-order cumulants. To illustrate the effectiveness of our methods, various simulation examples are presented.

Keywords: Cumulants, Identification, MA models, Parameter estimation

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100 On the Fast Convergence of DD-LMS DFE Using a Good Strategy Initialization

Authors: Y.Ben Jemaa, M.Jaidane

Abstract:

In wireless communication system, a Decision Feedback Equalizer (DFE) to cancel the intersymbol interference (ISI) is required. In this paper, an exact convergence analysis of the (DFE) adapted by the Least Mean Square (LMS) algorithm during the training phase is derived by taking into account the finite alphabet context of data transmission. This allows us to determine the shortest training sequence that allows to reach a given Mean Square Error (MSE). With the intention of avoiding the problem of ill-convergence, the paper proposes an initialization strategy for the blind decision directed (DD) algorithm. This then yields a semi-blind DFE with high speed and good convergence.

Keywords: Adaptive Decision Feedback Equalizer, PerformanceAnalysis, Finite Alphabet Case, Ill-Convergence, Convergence speed.

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99 Blind Image Deconvolution by Neural Recursive Function Approximation

Authors: Jiann-Ming Wu, Hsiao-Chang Chen, Chun-Chang Wu, Pei-Hsun Hsu

Abstract:

This work explores blind image deconvolution by recursive function approximation based on supervised learning of neural networks, under the assumption that a degraded image is linear convolution of an original source image through a linear shift-invariant (LSI) blurring matrix. Supervised learning of neural networks of radial basis functions (RBF) is employed to construct an embedded recursive function within a blurring image, try to extract non-deterministic component of an original source image, and use them to estimate hyper parameters of a linear image degradation model. Based on the estimated blurring matrix, reconstruction of an original source image from a blurred image is further resolved by an annealed Hopfield neural network. By numerical simulations, the proposed novel method is shown effective for faithful estimation of an unknown blurring matrix and restoration of an original source image.

Keywords: Blind image deconvolution, linear shift-invariant(LSI), linear image degradation model, radial basis functions (rbf), recursive function, annealed Hopfield neural networks.

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98 A Frequency Grouping Approach for Blind Deconvolution of Fairly Motionless Sources

Authors: E. S. Gower, T. Tsalaile, E. Rakgati, M. O. J. Hawksford

Abstract:

A frequency grouping approach for multi-channel instantaneous blind source separation (I-BSS) of convolutive mixtures is proposed for a lower net residual inter-symbol interference (ISI) and inter-channel interference (ICI) than the conventional short-time Fourier transform (STFT) approach. Starting in the time domain, STFTs are taken with overlapping windows to convert the convolutive mixing problem into frequency domain instantaneous mixing. Mixture samples at the same frequency but from different STFT windows are grouped together forming unique frequency groups. The individual frequency group vectors are input to the I-BSS algorithm of choice, from which the output samples are dispersed back to their respective STFT windows. After applying the inverse STFT, the resulting time domain signals are used to construct the complete source estimates via the weighted overlap-add method (WOLA). The proposed algorithm is tested for source deconvolution given two mixtures, and simulated along with the STFT approach to illustrate its superiority for fairly motionless sources.

Keywords: Blind source separation, short-time Fouriertransform, weighted overlap-add method

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97 Blind Non-Minimum Phase Channel Identification Using 3rd and 4th Order Cumulants

Authors: S. Safi, A. Zeroual

Abstract:

In this paper we propose a family of algorithms based on 3rd and 4th order cumulants for blind single-input single-output (SISO) Non-Minimum Phase (NMP) Finite Impulse Response (FIR) channel estimation driven by non-Gaussian signal. The input signal represents the signal used in 10GBASE-T (or IEEE 802.3an-2006) as a Tomlinson-Harashima Precoded (THP) version of random Pulse-Amplitude Modulation with 16 discrete levels (PAM-16). The proposed algorithms are tested using three non-minimum phase channel for different Signal-to-Noise Ratios (SNR) and for different data input length. Numerical simulation results are presented to illustrate the performance of the proposed algorithms.

Keywords: Higher Order Cumulants, Channel identification, Ethernet communication.

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96 An Improved Integer Frequency Offset Estimator using the P1 Symbol for OFDM System

Authors: Yong-An Jung, Young-Hwan You

Abstract:

This paper suggests an improved integer frequency offset (IFO) estimation scheme using P1 symbol for orthogonal frequency division multiplexing (OFDM) based the second generation terrestrial digital video broadcasting (DVB-T2) system. Proposed IFO estimator is designed by a low-complexity blind IFO estimation scheme, which is implemented with complex additions. Also, we propose active carriers (ACs) selection scheme in order to prevent performance degradation in blind IFO estimation. The simulation results show that under the AWGN and TU6 channels, the proposed method has low complexity than conventional method and almost similar performance in comparison with the conventional method.

Keywords: OFDM, DVB-T2, P1 symbol, ACs, IFO.

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95 Utilizing the Analytic Hierarchy Process in Improving Performances of Blind Judo

Authors: Hyun Chul Cho, Hyunkyoung Oh, Hyun Yoon, Jooyeon Jin, Jae Won Lee

Abstract:

Identifying, structuring, and racking the most important factors related to improving athletes’ performances could pave the way for improve training system. The purpose of this study was to identify the relative importance factors to improve performance of the of judo athletes with visual impairments, including blindness by using the Analytic Hierarchy Process (AHP). After reviewing the literature, the relative importance of factors affecting performance of the blind judo was selected. A group of expert reviewed the first draft of the questionnaires, and then finally selected performance factors were classified into the major categories of techniques, physical fitness, and psychological categories. Later, a pre-selected experts group was asked to review the final version of questionnaire and confirm the priories of performance factors. The order of priority was determined by performing pairwise comparisons using Expert Choice 2000. Results indicated that “grappling” (.303) and “throwing” (.234) were the most important lower hierarchy factors for blind judo skills. In addition, the most important physical factors affecting performance were “muscular strength and endurance” (.238). Further, among other psychological factors “competitive anxiety” (.393) was important factor that affects performance. It is important to offer psychological skills training to reduce anxiety of judo athletes with visual impairments and blindness, so they can compete in their optimal states. These findings offer insights into what should be considered when determining factors to improve performance of judo athletes with visual impairments and blindness.

Keywords: Analytic hierarchy process, blind athlete, judo, sport performance.

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94 Usability Issues of Smart Phone Applications: For Visually Challenged People

Authors: Anam Ashraf, Arif Raza

Abstract:

In this era of globalization, adoption of technology is quite difficult for people with physical disabilities compared to people with normal abilities. The advancement in mobile based accessible applications have opened up several different avenues for the visually challenged across the globe. Smartphones applications are not very common for blind people, but they access and use these applications in their daily lives to some extent. Several smartphone applications have a number of usability issues for the visually impaired. In this paper, we evaluate the usability of various android & iPhone applications for blind people through analysis and surveys. This paper aspires to provide guidance in order to increase smartphone application accessibility for the visually impaired. An abstract application design is also proposed to overcome usability issues in smartphone applications for visually challenged people.

Keywords: Eyes-free shell, human computer interaction, usability engineering, visually challenged.

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93 Algebraic Approach for the Reconstruction of Linear and Convolutional Error Correcting Codes

Authors: Johann Barbier, Guillaume Sicot, Sebastien Houcke

Abstract:

In this paper we present a generic approach for the problem of the blind estimation of the parameters of linear and convolutional error correcting codes. In a non-cooperative context, an adversary has only access to the noised transmission he has intercepted. The intercepter has no knowledge about the parameters used by the legal users. So, before having acess to the information he has first to blindly estimate the parameters of the error correcting code of the communication. The presented approach has the main advantage that the problem of reconstruction of such codes can be expressed in a very simple way. This allows us to evaluate theorical bounds on the complexity of the reconstruction process but also bounds on the estimation rate. We show that some classical reconstruction techniques are optimal and also explain why some of them have theorical complexities greater than these experimentally observed.

Keywords: Blind estimation parameters, error correcting codes, non-cooperative context, reconstruction algorithm

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92 Effect of Peak-to-Average Power Ratio Reduction on the Multicarrier Communication System Performance Parameters

Authors: Sanjay Singh, M Sathish Kumar, H. S Mruthyunjaya

Abstract:

Multicarrier transmission system such as Orthogonal Frequency Division Multiplexing (OFDM) is a promising technique for high bit rate transmission in wireless communication system. OFDM is a spectrally efficient modulation technique that can achieve high speed data transmission over multipath fading channels without the need for powerful equalization techniques. However the price paid for this high spectral efficiency and less intensive equalization is low power efficiency. OFDM signals are very sensitive to nonlinear effects due to the high Peak-to-Average Power Ratio (PAPR), which leads to the power inefficiency in the RF section of the transmitter. This paper investigates the effect of PAPR reduction on the performance parameter of multicarrier communication system. Performance parameters considered are power consumption of Power Amplifier (PA) and Digital-to-Analog Converter (DAC), power amplifier efficiency, SNR of DAC and BER performance of the system. From our analysis it is found that irrespective of PAPR reduction technique being employed, the power consumption of PA and DAC reduces and power amplifier efficiency increases due to reduction in PAPR. Moreover, it has been shown that for a given BER performance the requirement of Input-Backoff (IBO) reduces with reduction in PAPR.

Keywords: BER, Crest Factor (CF), Digital-to-Analog Converter(DAC), Input-Backoff (IBO), Orthogonal Frequency Division Multiplexing(OFDM), Peak-to-Average Power Ratio (PAPR), PowerAmplifier efficiency, SNR

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91 EPR Hiding in Medical Images for Telemedicine

Authors: K. A. Navas, S. Archana Thampy, M. Sasikumar

Abstract:

Medical image data hiding has strict constrains such as high imperceptibility, high capacity and high robustness. Achieving these three requirements simultaneously is highly cumbersome. Some works have been reported in the literature on data hiding, watermarking and stegnography which are suitable for telemedicine applications. None is reliable in all aspects. Electronic Patient Report (EPR) data hiding for telemedicine demand it blind and reversible. This paper proposes a novel approach to blind reversible data hiding based on integer wavelet transform. Experimental results shows that this scheme outperforms the prior arts in terms of zero BER (Bit Error Rate), higher PSNR (Peak Signal to Noise Ratio), and large EPR data embedding capacity with WPSNR (Weighted Peak Signal to Noise Ratio) around 53 dB, compared with the existing reversible data hiding schemes.

Keywords: Biomedical imaging, Data security, Datacommunication, Teleconferencing.

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90 Blind Impulse Response Identification of Frequency Radio Channels: Application to Bran A Channel

Authors: S. Safi, M. Frikel, M. M'Saad, A. Zeroual

Abstract:

This paper describes a blind algorithm for estimating a time varying and frequency selective fading channel. In order to identify blindly the impulse response of these channels, we have used Higher Order Statistics (HOS) to build our algorithm. In this paper, we have selected two theoretical frequency selective channels as the Proakis-s 'B' channel and the Macchi-s channel, and one practical frequency selective fading channel called Broadband Radio Access Network (BRAN A). The simulation results in noisy environment and for different data input channel, demonstrate that the proposed method could estimate the phase and magnitude of these channels blindly and without any information about the input, except that the input excitation is i.i.d (Identically and Independent Distributed) and non-Gaussian.

Keywords: Frequency response, system identification, higher order statistics, communication channels, phase estimation.

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89 An Efficient Separation for Convolutive Mixtures

Authors: Salah Al-Din I. Badran, Samad Ahmadi, Dylan Menzies, Ismail Shahin

Abstract:

This paper describes a new efficient blind source separation method; in this method we uses a non-uniform filter bank and a new structure with different sub-bands. This method provides a reduced permutation and increased convergence speed comparing to the full-band algorithm. Recently, some structures have been suggested to deal with two problems: reducing permutation and increasing the speed of convergence of the adaptive algorithm for correlated input signals. The permutation problem is avoided with the use of adaptive filters of orders less than the full-band adaptive filter, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each sub-band than the input signal at full-band, and can promote better rates of convergence.

Keywords: Blind source separation (BSS), estimates, full-band, mixtures, Sub-band.

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88 An Interlacing Technique-Based Blind Video Watermarking Using Wavelet

Authors: B. Sridhar, C. Arun

Abstract:

The rapid growth of multimedia technology demands the secure and efficient access to information. This fast growing lose the confidence of unauthorized duplication. Henceforth the protection of multimedia content is becoming more important. Watermarking solves the issue of unlawful copy of advanced data. In this paper, blind video watermarking technique has been proposed. A luminance layer of selected frames is interlaced into two even and odd rows of an image, further it is deinterlaced and equalizes the coefficients of the two shares. Color watermark is split into different blocks, and the pieces of block are concealed in one of the share under the wavelet transform. Stack the two images into a single image by introducing interlaced even and odd rows in the two shares. Finally, chrominance bands are concatenated with the watermarked luminance band. The safeguard level of the secret information is high, and it is undetectable. Results show that the quality of the video is not changed also yields the better PSNR values.

Keywords: Authentication, data security, deinterlaced, wavelet transform, watermarking.

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87 Blind Spot Area Tracking Solution Using 1x12 POF-Based Optical Couplers

Authors: Mohammad Syuhaimi Ab-Rahman, Mohd Hadi Guna Safnal, Mohd Hazwan Harun, Mohd.Saiful Dzulkefly Zan, Kasmiran Jumari

Abstract:

Optical 1x12 fused-taper-twisted polymer optical fiber (POF) couplers has been fabricated by a perform technique. Characterization of the coupler which proposed to be used in passive night vision application to tracking a blind sport area was reported. During the development process of fused-taper-twisted POF couplers was carried out, red LED fully utilized to be injected into the couplers to test the quality of fabricated couplers. Some characterization parameters, such as optical output power, POFs attenuation characteristics and power losses on the network were observed. The maximum output power efficiency of the coupler is about 40%, but it can be improved gradually through experience and practice.

Keywords: polymer optical fiber (POF), customer-made, fused-taper-twisted fiber, optical coupler, small world communication, home network.

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86 Wavelet Enhanced CCA for Minimization of Ocular and Muscle Artifacts in EEG

Authors: B. S. Raghavendra, D. Narayana Dutt

Abstract:

Electroencephalogram (EEG) recordings are often contaminated with ocular and muscle artifacts. In this paper, the canonical correlation analysis (CCA) is used as blind source separation (BSS) technique (BSS-CCA) to decompose the artifact contaminated EEG into component signals. We combine the BSSCCA technique with wavelet filtering approach for minimizing both ocular and muscle artifacts simultaneously, and refer the proposed method as wavelet enhanced BSS-CCA. In this approach, after careful visual inspection, the muscle artifact components are discarded and ocular artifact components are subjected to wavelet filtering to retain high frequency cerebral information, and then clean EEG is reconstructed. The performance of the proposed wavelet enhanced BSS-CCA method is tested on real EEG recordings contaminated with ocular and muscle artifacts, for which power spectral density is used as a quantitative measure. Our results suggest that the proposed hybrid approach minimizes ocular and muscle artifacts effectively, minimally affecting underlying cerebral activity in EEG recordings.

Keywords: Blind source separation, Canonical correlationanalysis, Electroencephalogram, Muscle artifact, Ocular artifact, Power spectrum, Wavelet threshold.

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85 Super Resolution Blind Reconstruction of Low Resolution Images using Wavelets based Fusion

Authors: Liyakathunisa, V. K. Ananthashayana

Abstract:

Crucial information barely visible to the human eye is often embedded in a series of low resolution images taken of the same scene. Super resolution reconstruction is the process of combining several low resolution images into a single higher resolution image. The ideal algorithm should be fast, and should add sharpness and details, both at edges and in regions without adding artifacts. In this paper we propose a super resolution blind reconstruction technique for linearly degraded images. In our proposed technique the algorithm is divided into three parts an image registration, wavelets based fusion and an image restoration. In this paper three low resolution images are considered which may sub pixels shifted, rotated, blurred or noisy, the sub pixel shifted images are registered using affine transformation model; A wavelet based fusion is performed and the noise is removed using soft thresolding. Our proposed technique reduces blocking artifacts and also smoothens the edges and it is also able to restore high frequency details in an image. Our technique is efficient and computationally fast having clear perspective of real time implementation.

Keywords: Affine Transforms, Denoiseing, DWT, Fusion, Image registration.

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84 Bifidobacterium lactis Fermented Milk Was Not Effective for Helicobacter pylori Eradication: A Prospective, Randomized, Double-Blind, Controlled Study

Authors: R. C. Barbuti, M. N. Oliveira, N. P. Perina, C. Haro, P. Bosch, C. S. Bogsan, J. N. Eisig, T. Navarro-Rodriguez

Abstract:

The management of Helicobacter pylori (H. pylori) eradication is still a matter of discussion, full effectiveness is rarely achieved, and it has many adverse effects. The use of probiotics may be associated with better eradication rates and possibly prevention of adverse events due to antibiotic therapy. The present clinical study was undertaken to evaluate the efficacy of a specially designed fermented milk product, containing Bifidobacterium lactis B420, on the eradication of H. pylori infection in a prospective, randomized, double-blind, controlled study in humans. Four test fermented milks (FM) were specially designed in which counts of viable cells in all products were 10^10 Log CFU. 100 mL-1 for Bifidobacterium lactis - Bifidobacterium species 420. 190 subjects infected with H. pylori, with previous diagnosis of functional dyspepsia according to Rome III criteria entered the study. Bifidobacterium lactis B420, administered twice a day for 90 days was not able to eradicate H. pylori in Brazilian patients with functional dyspepsia.

Keywords: Antibacterial Therapy, Bifidobacteria Fermented milk, Helicobacter pylori, probiotics.

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83 MIMO-OFDM Channel Tracking Using a Dynamic ANN Topology

Authors: Manasjyoti Bhuyan, Kandarpa Kumar Sarma

Abstract:

All the available algorithms for blind estimation namely constant modulus algorithm (CMA), Decision-Directed Algorithm (DDA/DFE) suffer from the problem of convergence to local minima. Also, if the channel drifts considerably, any DDA looses track of the channel. So, their usage is limited in varying channel conditions. The primary limitation in such cases is the requirement of certain overhead bits in the transmit framework which leads to wasteful use of the bandwidth. Also such arrangements fail to use channel state information (CSI) which is an important aid in improving the quality of reception. In this work, the main objective is to reduce the overhead imposed by the pilot symbols, which in effect reduces the system throughput. Also we formulate an arrangement based on certain dynamic Artificial Neural Network (ANN) topologies which not only contributes towards the lowering of the overhead but also facilitates the use of the CSI. A 2×2 Multiple Input Multiple Output (MIMO) system is simulated and the performance variation with different channel estimation schemes are evaluated. A new semi blind approach based on dynamic ANN is proposed for channel tracking in varying channel conditions and the performance is compared with perfectly known CSI and least square (LS) based estimation.

Keywords: MIMO, Artificial Neural Network (ANN), CMA, LS, CSI.

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82 Toward Indoor and Outdoor Surveillance Using an Improved Fast Background Subtraction Algorithm

Authors: A. El Harraj, N. Raissouni

Abstract:

The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes invariance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.

Keywords: Video surveillance, background subtraction, Contrast Limited Histogram Equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes.

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81 Two Different Solutions for Gigabit Ethernet Transmission over POF

Authors: Stefano Straullu, Silvio Abrate, Antonino Nespola, Paolo Savio, Roberto Gaudino

Abstract:

Two completely different approaches for a Gigabit Ethernet compliant stream transmission over 50m of 1mm PMMA SI-POF have been experimentally demonstrated and are compared in this paper. The first solution is based on a commercial RC-LED transmission and a careful optimization of the physical layer architecture, realized during the POF-PLUS EU Project. The second solution exploits the performance of an edge-emitting laser at the transmitter side in order to avoid any sort of electrical equalization at the receiver side.

Keywords: Gigabit Ethernet, Home Networking, Step-Index Polymer Optical Fiber (SI-POF)

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80 Blind Source Separation for Convoluted Signals Based on Properties of Acoustic Transfer Function in Real Environments

Authors: Takaaki Ishibashi

Abstract:

Frequency domain independent component analysis has a scaling indeterminacy and a permutation problem. The scaling indeterminacy can be solved by use of a decomposed spectrum. For the permutation problem, we have proposed the rules in terms of gain ratio and phase difference derived from the decomposed spectra and the source-s coarse directions. The present paper experimentally clarifies that the gain ratio and the phase difference work effectively in a real environment but their performance depends on frequency bands, a microphone-space and a source-microphone distance. From these facts it is seen that it is difficult to attain a perfect solution for the permutation problem in a real environment only by either the gain ratio or the phase difference. For the perfect solution, this paper gives a solution to the problems in a real environment. The proposed method is simple, the amount of calculation is small. And the method has high correction performance without depending on the frequency bands and distances from source signals to microphones. Furthermore, it can be applied under the real environment. From several experiments in a real room, it clarifies that the proposed method has been verified.

Keywords: blind source separation, frequency domain independent component analysys, permutation correction, scale adjustment, target extraction.

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79 On the Symbol Based Decision Feedback Equalizer

Authors: Mohammed Nafie

Abstract:

Decision Feedback equalizers (DFEs) usually outperform linear equalizers for channels with intersymbol interference. However, the DFE performance is highly dependent on the availability of reliable past decisions. Hence, in coded systems, where reliable decisions are only available after decoding the full block, the performance of the DFE will be affected. A symbol based DFE is a DFE that only uses the decision after the block is decoded. In this paper we derive the optimal settings of both the feedforward and feedback taps of the symbol based equalizer. We present a novel symbol based DFE filterbank, and derive its taps optimal settings. We also show that it outperforms the classic DFE in terms of complexity and/or performance.

Keywords: Coding, DFE, Equalization, Exponential Channelmodels.

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78 Increasing Convergence Rate of a Fractionally-Spaced Channel Equalizer

Authors: Waseem Khan

Abstract:

In this paper a technique for increasing the convergence rate of fractionally spaced channel equalizer is proposed. Instead of symbol-spaced updating of the equalizer filter, a mechanism has been devised to update the filter at a higher rate. This ensures convergence of the equalizer filter at a higher rate and therefore less time-consuming. The proposed technique has been simulated and tested for two-ray modeled channels with various delay spreads. These channels include minimum-phase and nonminimum- phase channels. Simulation results suggest that that proposed technique outperforms the conventional technique of symbol-spaced updating of equalizer filter.

Keywords: Channel equalization, Fractionally-spaced equalizer

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