The work proposes an optimization-based robust adaptive gain sliding mode control technique to handle bounded behavior of uncertainties/perturbations without having the exact knowledge of the bound a priori. The const...
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The work proposes an optimization-based robust adaptive gain sliding mode control technique to handle bounded behavior of uncertainties/perturbations without having the exact knowledge of the bound a priori. The constant of the sliding surface follows dynamical adaptive nature using three optimization techniques, i.e. Harmony searchalgorithm, Bacterial Foraging Optimization algorithm and gradient search algorithm to extenuate the extent of chattering. The gain of the switching control law, which is a part of the sliding mode control design, is calculated using the gain adaption technique. Lyapunov Stability Criterion is applied to assure the stability of the closed-loop system with adaptable gain and the optimized value of the sliding constant. An inverted Pendulum system has been taken to validate the proposition both in the simulation environment and the hardware platform.
Photonic crystal fibers, also known as microstructured or holey fibers generated great interest in the scientific community. Today, Index Guided photonic crystal fibers (PCFs) are established as an alternative fiber t...
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Photonic crystal fibers, also known as microstructured or holey fibers generated great interest in the scientific community. Today, Index Guided photonic crystal fibers (PCFs) are established as an alternative fiber technology. Index Guided PCF addicted to challenges that reduce its durability and sensitivity of numerous PCF sensors according to their application field. Challenges may be in terms of polarization dispersion which arises due to Random imperfections that break the circular symmetry in PCF. To cope up with the above challenges, this work has proposed a Predictive Feedback Polarized Dispersion Control Model. Our model process with predictive feedback optimized error solution using Nonlinear Model Predictive Controller along with gradient search algorithm, which controls the polarization dispersion based on the Sequential Approach. A sequential approach is used here, to detect and separate the overlapped waves. Also, the Finite Element Analysis method has been accomplished to perform numerical analysis. Thus our model enhances the system performance in terms of Dispersion, Refractive Index, Confinement Loss, and Sensitivity.
Osteoporosis classification is a significant requirement in the medical field to automatically classify the patients with skeleton disorder that occurs as a result of aging. The classification algorithms required impr...
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Osteoporosis classification is a significant requirement in the medical field to automatically classify the patients with skeleton disorder that occurs as a result of aging. The classification algorithms required improved accuracy and computationally less complexity. Accordingly, this paper proposes a classification method using the proposed gradient harmony search (GHS) optimization-based deep belief network. The GHS is developed by integrating the harmony search (HS) in the gradient descent (GD) algorithm. The osteoporosis classification is progressed as five major steps: preprocessing, segmentation using active shape model, geometric estimation using the proposed template search method, feature extraction for extracting the medical and image level features, and osteoporosis classification using the proposed GHS based deep belief network. The proposed template search method updates the geometric points of the femur segment effectively and automatically. Experimentation using the real-time database ensures the effectiveness of the proposed method in terms of accuracy, sensitivity, and specificity. The proposed method acquired the accuracy of 0.9539, proving that the osteoporosis classification using the proposed algorithm seems to be effective in taking accurate decisions regarding the patients.
This paper introduces two algorithms of the phase retrieval, Gerchberg-Saxton algorithm and gradient search algorithm. We respectively get the function of the object of gradient search algorithm about the generalized ...
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This paper introduces two algorithms of the phase retrieval, Gerchberg-Saxton algorithm and gradient search algorithm. We respectively get the function of the object of gradient search algorithm about the generalized pupil, wavefront and the zernike coefficients of the partial derivatives when double-frame images and their defocus as the input. The relationship between GS algorithm and the gradient search algorithm are revealed. This paper designs the simulation experiment with GS algorithm and gradient search algorithm when single-frame images and double-frame images are used as input. The experiment results show that the gradient search algorithm is superior to GS algorithm for a single-frame image as input. Both GS algorithm and gradient search algorithm can primely work out wavefront for double frame images of different defocus as the input, but the convergence rate of gradient search algorithm is evidently better than GS algorithm. (C) 2015 Elsevier GmbH. All rights reserved.
Compact arrays are known to be associated with antenna coupling and noise correlation. The noise can be either antenna noise, LNA noise or downstream noise. Due to these effects, it was shown that the matching network...
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ISBN:
(纸本)9781479930838
Compact arrays are known to be associated with antenna coupling and noise correlation. The noise can be either antenna noise, LNA noise or downstream noise. Due to these effects, it was shown that the matching network affects the performance of MIMO systems with coupled receiver antennas. Since the optimal multiport matching network is of very high complexity as well as very narrow operation bandwidth, development of single-port (SP) matching networks that boost the performance became inevitable. In this paper we develop a gradient-searchalgorithm to design the matching network for achievable rate maximization of multi user MIMO systems. For arty combination of noise sources, we rigorously derive the exact gradient of the achievable rate with respect to the components of the matching network. We assume either full knowledge of the spatial channel or knowing its statistical properties. In the later case we optimize the matching network to maximize the Jensen's bound. Substantial performance enhancement is shown when our algorithms are used. Significant reduction in the array area is gained in comparison to the often used lambda/2 antenna spacing without taking coupling into account. This can be vital for future wireless systems adopting massive MIMO arrays. Via eigenvalues distribution simulations at different SNR regimes, we show an intuitive link to the communication theory.
The phase retrieval hybrid algorithm based on gradient search algorithm and GS algorithm is designed for surface testing of the high dynamic range error beyond one wavelength after the rough polish process. Phase retr...
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ISBN:
(纸本)9781628413571
The phase retrieval hybrid algorithm based on gradient search algorithm and GS algorithm is designed for surface testing of the high dynamic range error beyond one wavelength after the rough polish process. Phase retrieval is a wave front sensing method that uses the intensity distribution to reconstruct the phase distribution of optical field. In the rough polish process of optical surface testing, there is the problem of phase wrapping caused by the high dynamic range error, which makes it hard to be measured by interferometers. In this condition, infrared interferometers are widely used for optical testing, but the operation of infrared interferometer is complicated because of the invisibility of infrared light and it's very sensitive to the temperature, vibration and turbulence. The phase retrieval hybrid algorithm derives from gradient search algorithm and GS algorithm, aiming to solve the problem of phase wrapping caused by the high dynamic range error. Firstly, phase distribution is described by Zernike polynomials and the coefficients of Zernike polynomials are optimized by the gradient search algorithm to retrieve the low frequency error beyond one wavelength. Then GS algorithm is used to retrieve the high frequency error of small value. In the simulated calculation, the hybrid algorithm is used for surface testing of a spherical mirror with PV 2.42 lambda, RMS 0.41 lambda. The retrieved surface is PV 2.53 lambda, RMS 0.42 lambda. The simulation result shows that the hybrid algorithm is effective and accurate for optical surface testing of high dynamic range error.
Estimation of channel fading parameters is an important task in the design of communication links such as in maximum ratio combining (MRC), where the SNR of the link has to be estimated. The maximum combining weights ...
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ISBN:
(纸本)9780819471710
Estimation of channel fading parameters is an important task in the design of communication links such as in maximum ratio combining (MRC), where the SNR of the link has to be estimated. The maximum combining weights are directly related to the SNR or the fading channel coefficients. In this paper, we propose iterative techniques based on Maximum Likelihood parameter estimation to estimate the parameters of Nakagami-m distribution in the presence of additive white Gaussian noise. We show that the proposed iterative algorithms converge to a unique solution independent of the initial condition. However, for the purpose of fast convergence, a method is used to find an initial condition close to the true solution. This initial condition is obtained by solving for the unique positive root of a polynomial. Comparisons of our proposed approaches are made with respect to the noise and initial conditions. The performance of the algorithm with respect to the Cramer-Rao bound (CRB) is investigated. Computer simulation results for different signal to noise ratios (SNR) are presented.
In this paper, we propose an automatic method of designing digital filters for three-dimensional (3-D) sound movement that is dedicated to embedded applications. By this method, read-only memory (ROM) capacity and com...
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In this paper, we propose an automatic method of designing digital filters for three-dimensional (3-D) sound movement that is dedicated to embedded applications. By this method, read-only memory (ROM) capacity and computational load are reduced with only slight degradation of the 3-D sound effect. For practical applications of 3-D sound, the continuous movement of a virtual sound image is indispensable. To achieve 3-D sound movement, the interpolation of filter coefficients is often required;however, the frequency response of an intermediate filter obtained by interpolation is severely distorted using conventional automatic design methods. The proposed method reduces this distortion by evaluating the response of the intermediate filters in the optimization process. The results of objective evaluation and subjective listening tests show that the proposed method improves the perceptual quality of 3-D sound movement, even with runtime interpolation of filter coefficients.
The application of genetic algorithm for computer-aided design and optimisation of microwave circuits Is presented using the example of three section Quarter wave transmission line transformers. The circuit chosen In ...
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The application of genetic algorithm for computer-aided design and optimisation of microwave circuits Is presented using the example of three section Quarter wave transmission line transformers. The circuit chosen In this paper is a classic example to compare different optimisation algorithms[1]. Two different optimisation methods gradient search algorithm and genetic algorithm have been used for the optimisation. It has been found that the optimisation method based on genetic algorithm is very robust for the optimisation of microwave circuits.
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