Recent Submissions

Now showing 1 - 5 of 16
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    Speech Emotion Recognition using Unsupervised Feature Selection Algorithms
    (Společnost pro radioelektronické inženýrství, 2020-06) Bandela, Surekha Reddy; Kumar, T. Kishore
    The use of the combination of different speech features is a common practice to improve the accuracy of Speech Emotion Recognition (SER). Sometimes, this leads to an abrupt increase in the processing time and some of these features contribute less to emotion recognition often resulting in an incorrect prediction of emotion with which the accuracy of the SER system decreases substantially. Hence, there is a need to select the appropriate feature set that can contribute significantly to emotion recognition. This paper presents the use of Feature Selection with Adaptive Structure Learning (FSASL) and Unsupervised Feature Selection with Ordinal Locality (UFSOL) algorithms for feature dimension reduction. A novel Subset Feature Selection (SuFS) algorithm is proposed to further reduce the feature dimension and achieve a comparable better accuracy when used along with the FSASL and UFSOL algorithms. 1582 INTERSPEECH 2010 Paralinguistic, 20 Gammatone Cepstral Coefficients and Support Vector Machine classifier with 10-Fold Cross-Validation and Hold-Out Validation are considered in this work. The EMO-DB and IEMOCAP databases are used to evaluate the performance of the proposed SER system in terms of Classification accuracy and Computational Time. From the result analysis, it is evident that the proposed SER system outperforms the existing ones.
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    Suppressing the Effect of Impulsive Noise on Millimeter-Wave Communications Systems
    (Společnost pro radioelektronické inženýrství, 2020-06) Shhab, Lara; Rizaner, Ahmet; Ulusoy, Ali Hakan; Amca, Hasan
    The Fifth Generation (5G) wireless communication systems are expected to satisfy higher data rates, network scalability, increasing number of connections and higher traffic densities in a cost-effective manner. The key essence of 5G technology resides in exploring the frequency bands at millimeter-Wave (mmWave) frequencies. As is well known, the presence of Impulsive Noise (IN) corrupts signals and leads to increased Bit Error Rate (BER) and decreased spectral efficiency. In this paper, the performance of mmWave systems in multi-path fading channel and IN is studied and a new thresholding mechanism for the clipping and blanking filters to suppress the impulsive components of noise is suggested. The paper also presents the mathematical expressions to determine the optimum threshold selection for the filters. Simulation results show that use of clipping and blanking filters with the optimal threshold values reduces the adverse effect of IN and improves system performance significantly.
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    A Multi-Reconfigurable CLL-Loaded Planar Monopole Antenna
    (Společnost pro radioelektronické inženýrství, 2020-06) Fakharian, Mohammad M.; Rezaei, Pejman; Orouji, Ali A.
    In this paper, multi-reconfiguration capabilities of a planar monopole antenna with two switchable capacitively loaded loops (CLLs), as near field resonant parasitic elements, are introduced. The idea is to apply the CLLs not only to minimize the dimensions of the antenna, but also to present multiple resonances, which can be satisfactorily chosen by applying switches placed across six gaps of the CLLs. By changing the switched states, it is feasible to obtain different reconfigurations such as frequency agility (from 1.5 to 2.9 GHz), polarization diversity (with circular polarization bandwidth from 1.59 to 1.72 GHz), and various shapes of the radiation patterns and beam directions (change in the ±30° y-direction) of the antenna. The transmutation of polarization designs from their linear counterparts to left hand and right hand circular polarizations by introducing an asymmetry in the configuration of the two-CLLs is also represented. The prototypes of the proposed antenna are fabricated and tested. The measured reflection coefficient, radiation pattern, gain and axial ratio results are presented and compared to the corresponding simulated values.
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    Underdetermined Direction-of-Arrival Estimation with Coprime Array via Atomic Norm Minimization
    (Společnost pro radioelektronické inženýrství, 2020-06) Pan, Yujian; Yao, Min; Luo, Guo Qing; Pan, Bai Cao; Gao, Xiaoxin
    The coprime array provides the possibility of resolving more signals than the sensors for the direction-of-arrival (DOA) estimation application. However, the non-consecution of its virtual array raises challenges for making full use of the degree of freedom (DOF). In this paper, we propose a new underdetermined DOA estimation method with coprime array where the non-consecutive virtual array can be converted into a virtual uniform linear array (ULA) with the same aperture. Firstly, all elements in the vectorized signal covariance matrix corresponding to the same virtual array positions are averaged to construct the output signals of the virtual array. Then, an atomic norm minimization (ANM) based optimization problem is formed for denoising the output signals of the virtual array and for interpolating the missing signals at the virtual array holes. At last, the ANM problem is solved by the semidefinite programming (SDP) and the DOAs are obtained by applying the subspace method on the reconstructed signal covariance matrix of the interpolated virtual ULA. The proposed algorithm is gridless and makes full use of the DOF and the information provided by the coprime array. The simulation results compared with the other representative methods are given to demonstrate the superiority of the proposed method with respect to the resolution and estimation accuracy.
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    Sliding Window Evaluation of the Wiener-Hopf Equation
    (Společnost pro radioelektronické inženýrství, 2020-06) Kraker, Alfred; Csuka, Barna; Kollar, Zsolt
    This paper presents an efficient method for solving the Wiener-Hopf equation in a sliding window by calculating the correlation matrices recursively. Furthermore, a novel algorithm is introduced for evaluating the inverse of the auto-correlation matrix - the Recursion with Splitting the Correlation matrix into 4 Blocks for Inversion - which can significantly reduce the computational requirements. The presented procedure is optimized for special cases to achieve an efficient implementation which allows faster rel-time signal processing or to reduce the response time - e.g. the latency -- by distributing the computations over the time. The proposed method is also validated through numerical simulations and hardware implementation.