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    • List of Articles Mohammad Reza Karami-Mollaei

      • Open Access Article

        1 - Speech Intelligibility Improvement in Noisy Environments for Near-End Listening Enhancement
        Peyman Goli Mohammad Reza Karami-Mollaei
        A new speech intelligibility improvement method for near-end listening enhancement in noisy environments is proposed. This method improves speech intelligibility by optimizing energy correlation of one-third octave bands of clean speech and enhanced noisy speech without More
        A new speech intelligibility improvement method for near-end listening enhancement in noisy environments is proposed. This method improves speech intelligibility by optimizing energy correlation of one-third octave bands of clean speech and enhanced noisy speech without power increasing. The energy correlation is determined as a cost function based on frequency band gains of the clean speech. Interior-point algorithm which is an iterative procedure for the nonlinear optimization is used to determine the optimal points of the cost function because of nonlinearity and complexity of the energy correlation function. Two objective intelligibility measures, speech intelligibility index and short-time objective intelligibility measure, are employed to evaluate the noisy enhanced speech intelligibility. Furthermore, the speech intelligibility scores are compared with unprocessed speech and a baseline method under various noisy conditions. The results show large intelligibility improvements with the proposed method over the unprocessed noisy speech. Manuscript profile
      • Open Access Article

        2 - Online Signature Verification: a Robust Approach for Persian Signatures
        Mohamamd Esmaeel Yahyatabar Yasser  Baleghi Mohammad Reza Karami-Mollaei
        In this paper, the specific trait of Persian signatures is applied to signature verification. Efficient features, which can discriminate among Persian signatures, are investigated in this approach. Persian signatures, in comparison with other languages signatures, have More
        In this paper, the specific trait of Persian signatures is applied to signature verification. Efficient features, which can discriminate among Persian signatures, are investigated in this approach. Persian signatures, in comparison with other languages signatures, have more curvature and end in a specific style. Usually, Persian signatures have special characteristics, in terms of speed, acceleration and pen pressure, during drawing curves. An experiment has been designed to determine the function indicating the most robust features of Persian signatures. Results obtained from this experiment are then used in feature extraction stage. To improve the performance of verification, a combination of shape based and dynamic extracted features is applied to Persian signature verification. To classify these signatures, Support Vector Machine (SVM) is applied. The proposed method is examined on two common Persian datasets, the new proposed Persian dataset in this paper (Noshirvani Dynamic Signature Dataset) and an international dataset (SVC2004). For three Persian datasets EER value are equal to 3, 3.93, 4.79, while for SVC2004 the EER value is 4.43. Manuscript profile
      • Open Access Article

        3 - A new Sparse Coding Approach for Human Face and Action Recognition
        Mohsen Nikpoor Mohammad Reza Karami-Mollaei Reza Ghaderi
        Sparse coding is an unsupervised method which learns a set of over-complete bases to represent data such as image, video and etc. In the cases where we have some similar images from the different classes, using the sparse coding method the images may be classified into More
        Sparse coding is an unsupervised method which learns a set of over-complete bases to represent data such as image, video and etc. In the cases where we have some similar images from the different classes, using the sparse coding method the images may be classified into the same class and devalue classification performance. In this paper, we propose an Affine Graph Regularized Sparse Coding approach for resolving this problem. We apply the sparse coding and graph regularized sparse coding approaches by adding the affinity constraint to the objective function to improve the recognition rate. Several experiments has been done on well-known face datasets such as ORL and YALE. The first experiment has been done on ORL dataset for face recognition and the second one has been done on YALE dataset for face expression detection. Both experiments have been compared with the basic approaches for evaluating the proposed method. The simulation results show that the proposed method can significantly outperform previous methods in face classification. In addition, the proposed method is applied to KTH action dataset and the results show that the proposed sparse coding approach could be applied for action recognition applications too. Manuscript profile
      • Open Access Article

        4 - SQP-based Power Allocation Strategy for Target Tracking in MIMO Radar Network with Widely Separated Antennas
        Mohammad  Akhondi Darzikolaei Mohammad Reza Karami-Mollaei Maryam Najimi
        MIMO radar with widely separated antennas enhances detection and estimation resolution by utilizing the diversity of the propagation path. Each antenna of this type of radar can steer its beam independently towards any direction as an independent transmitter. However, t More
        MIMO radar with widely separated antennas enhances detection and estimation resolution by utilizing the diversity of the propagation path. Each antenna of this type of radar can steer its beam independently towards any direction as an independent transmitter. However, the joint processing of signals for transmission and reception differs this radar from the multistatic radar. There are many resource optimization problems which improve the performance of MIMO radar. But power allocation is one of the most interesting resource optimization problems. The power allocation finds an optimum strategy to assign power to transmit antennas with the aim of minimizing the target tracking errors under specified transmit power constraints. In this study, the performance of power allocation for target tracking in MIMO radar with widely separated antennas is investigated. Therefore, a MIMO radar with distributed antennas is configured and a target motion model using the constant velocity (CV) method is modeled. Then Joint Cramer Rao bound (CRB) for target parameters (joint target position and velocity) estimation error is calculated. This is utilized as a power allocation problem objective function. Since the proposed power allocation problem is nonconvex. Therefore, a SQP-based power allocation algorithm is proposed to solve it. In simulation results, the performance of the proposed algorithm in various conditions such as a different number of antennas and antenna geometry configurations is examined. Results affirm the accuracy of the proposed algorithm. Manuscript profile