<span>This paper investigated the performance of the sliding mode control technique for dc/dc converter using frequency response method. The applications of the step down type switching regulator) buck converter (are found in the devices that use batteries as power source like laptop, cell phones, electric vehicle, and recently, it has also been used in the renewable energy processing, as a maximum output power can be achieved at higher efficiency. In order to optimize the efficiency and for convenient power management, the issues like power on transients, the effect of load variation, Switching and Electromagnetic interference (EMI) losses has to be overcome for which controllers are used. In the proposed method, pulse width modulation (PWM) based on proportional-integral-derivative sliding mode voltage controller (PID SMVC) is designed for a buck converter and the response for appropriate control parameters has been obtained. The system stability has been examined and analyzed from the performance characteristics, which shows clearly that the buck converter controlled by the sliding mode controller has fast dynamic response and it’s very efficient for various applications.</span>
<p><span lang="EN-GB">In this paper, different feature extraction and feature normalization methods are investigated for speaker recognition. With a view to give a good representation of acoustic speech signals, Power Normalized Cepstral Coefficients (PNCCs) and Mel Frequency Cepstral Coefficients (MFCCs) are employed for feature extraction. Then, to mitigate the effect of linear channel, Cepstral Mean-Variance Normalization (CMVN) and feature warping are utilized. The current paper investigates Text-independent speaker identification system by using 16 coefficients from both the MFCCs and PNCCs features. Eight different speakers are selected from the GRID-Audiovisual database with two females and six males. The speakers are modeled using the coupling between the Universal Background Model and Gaussian Mixture Models (GMM-UBM) in order to get a fast scoring technique and better performance. The system shows 100% in terms of speaker identification accuracy. The results illustrated that PNCCs features have better performance compared to the MFCCs features to identify females compared to male speakers. Furthermore, feature wrapping reported better performance compared to the CMVN method. </span></p>
In many modern GPR systems, it is desired to detect the presence of targets in the interference which includes clutter and noise. Detection of water leaks using GPR has been aimed in this work. Pipe and soil are known as the clutter of data in this scenario. Various signal processing techniques like multivariate subspace-based algorithms are proposed to effectively suppress the clutter and increase the signal to interference ratio. Combining Independent Component Analysis (ICA) and Principal Component Analysis (PCA) as a unique algorithm has demonstrated the ability to eliminate the GPR clutter and extract the target signal.
<span>In this paper, a photovoltaic (PV) fuzzy maximum power point tracking (MPPT) method optimized by the chimp algorithm is presented. The fuzzy logic controller (FLC) of seven triangular membership functions (MFs) is used. The optimization fitness function is composed of transient and steady-state indices under different irradiation and temperature operating conditions. By using MATLAB package, the performance of optimized method is examined and compared with asymmetrical FLC and well-known perturb and observe (P&O) tracking methods at different operating conditions in terms of: transient rising time (tr) and energy yield during 30 s. Moreover, the tracking methods are also compared in terms of the fitness <span>function value. From the comparison of simulation results, a more energy can be</span> harvested by using the proposed optimized tracking method compared to the <span>other methods. Consequently, at the various operating conditions, the proposed</span> method can be used as a more reliable tracking method for PV systems.</span>
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