Said Safi

Approach of facial surfaces by contour

In this work we have made a face recognition system based on the analysis of facial surfaces by analyzing the contours extracted from the 3D representation of human faces, called facial curves. Our recognition system uses the face representation of the image to the gray level as 2D surface in 3D space, with the third coordinate proportional to the intensity values of pixels. To extract the feature vector of face we used the method of analysis of facial curves. This approach is based on the mathematical definition of the space of facial surfaces. In this space the deformations are modeled by the geodesic path between two facial surfaces. The proposed method has been used for face recognition and tested on the database of face images known ORL database, developed by AT & T Laboratories Cambridge University in England, was used to evaluate the performance of our method under conditions where the pose and sample size are varied.

BER analysis of parallel and successive interference cancellation employing MMSE equalizer for MC-CDMA systems

This paper introduces a parallel/sucessive interference cancellation scheme for multi-carriers code-division multiple access (MC-COMA) in the case of a downlink transmission, that reduces the degrading effect on the desired user of interference from the other users who share the same channel. The implementation complexity of the scheme is linear in the number of users and operates on the fact that parallel processing simultaneously removes from each user a part of the interference produced by the remaining users accessing the channel the amount being proportional to their reliability. The parallel processing can be done in multiple stages. The proposed scheme uses an hybrid interference cancellation combining the advantages of these two schemes: parallel interference cancellation (PIC) and successive interference cancellation (SIC). The hybrid scheme (S-PIC) is faster, reliable and it reduces the computational load. Simulation results are given for different scenarios.

DOA estimation with fourth order propagator

In this paper, we derive a new propagator operator for estimating the Angles Of Arrival (AOA) of farfield narrowband electromagnetic waves impinging on antenna array when its number of sensors is larger than the number of radiating sources. The fourth order partition, of the array steering matrix, is presented to estimate the noise subspace using non diagonal partial cross correlation sub-matrices without the eigendecomposition while using all the sensors of the antenna. The Simulation results in presence of an additive white noise and real symmetric Toeplitz noise proved the efficiency of the proposed method comparatively to the ESPRIT estimator.

Two-Dimensional Face Recognition Methods Comparing with a Riemannian Analysis of Iso-Geodesic Curves

In this paper, the authors performed a comparative study of two-dimensional face recognition methods. This study was based on existing methods PCA, LDA, 2DPCA, 2DLDA, SVM... and 2D face surface analysis using a Riemannian geometry. The last system uses the representation of the image at gray level as a 2D surface in a 3D space where the third coordinate represent the intensity values of the pixels. The authors approach is to represent the human face as a collection of closed curves, called facial curves, and apply tools from the analysis of the shape of curves using the Riemannian geometry. Their application has been tested on two well-known databases of face images ORL and YaleB. ORL data base was used to evaluate the performance of their method when the pose and sample size are varied, and the database YaleB was used to examine the performance of the system when the facial expressions and lighting are varied.

Blind identification of indoor broadband radio access network using cumulants

This paper describes a blind algorithm for estimating a time varying and frequency selective fading channel, representing the Indoor Broadband Radio Access Network. In order to identify blindly the impulse response of this channel, we have used Higher Order Statistics (HOS). or cumulants, to build our algorithm. witch is compared with the Zhangs one. The simulation results, in presence of colored noise and for different data input channel. demonstrate that the proposed algorithm give good estimation of the phase and magnitude. comparing to the Zhaugs, one of these channels blindly (i.e without any information about the input), except that the input excitation is i.i.d (Identically and Independent Distributed) and non-Gaussian.

Channel Identification and Equalization based on Kernel Methods for Downlink Multicarrier-CDMA Systems

In this paper the authors are focused on channel identification and equalization for Multi-Carrier Code Division Multiple Access MC-CDMA system. For this, they identify the impulse response of two practical selective frequency fading channels called Broadband Radio Access Network BRAN A and BRAN B normalized by the European Telecommunications Standards Institute ETSI. To identify the channel parameters, they have the positive definite kernels to build on algorithm. The simulations show that the presented method confirms the good performance for different SNR values. In part of equalization, the authors use the Zero Forcing ZF and Minimum Mean Square Error MMSE equalizers.

Blind identification and equalization of channel based on higher-order cummulants: Application of MC-CDMA systems

In each communication system an identification of the transmission channel between the transmitter and the receiver, it is necessary to identify the parameters of channel. Several methods exist, the most commonly used methods are learning by sending occasionally a known sequence between the transmitter and the receiver. In order to solve the problem of channels identification and save the resource of bandwidth, we use blind techniques which are a great interest to have the best compromise between a suitable bit rate and quality of the information retrieved. In this paper we describe tree blind algorithms witch are based on high order cumulant (HOC). In order to identify the impulse of two selective frequency fading channels called Broad Radio Access Network (BRAN A and BRAN E). Our contribution in this work is to make a comparative study between different algorithms of blind identification, compared with a supervised such as RLS algorithm. The simulation results are in a noisy environment with different SNR, demonstrate that the proposed algorithm is better to estimate blindly the impulse response of these channels (without any information about the input).

Identification of Broadband Radio Access Network using the Takagui-Sugeno fuzzy systems and Higher Order Statistics

In this paper, we consider the problem of selective radio channel identification. Two technics are used, the first one is based on Higher Order Statistics (HOS), the second is based on Takagui-Sugeno (TS) fuzzy systems. In order to evaluate the proposed algorithms, we have used two practical selective frequency fading channels called Broadband Radio Access Network (BRAN A and BRAN E) normalized for MC-CDMA systems are considered to perform the proposed technics. The simulation results, for different Signal to Noise Ratio (SNR), demonstrates that: the algorithm based on Higher Order Statistics (HOS) is more efficiency than the TS algorithms in noisy environment - smallest SNR- but the TS algorithm more efficient than the HOS algorithms for highest SNR values.