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Highlights • DWT is used after framing the signal. • Sub-sampling into segments for correlation before applying DCT. • Arnold transform is employed to save detection security. • The fully blind detection is accomplished without using the original signal. • Sub-sampling abates robustness against re-sampling attack, increases imperceptibility. Abstract In this paper we propose a new scheme for blind watermarking of speech and audio signals. We used the discrete wavelet transform (DWT) after framing the signal, and then we applied the discrete cosine transform (DCT) on each frame. For correlation purpose, sub-sampling is performed to decompose the frame into two segments. For security concern, Arnold transform is employed on the watermark image in order to save detection security. The fully blind detection is accomplished without using the original speech/audio signal and the insertion parameter is not required. Experimental assessment and comparisons with other published schemes demonstrate a good tradeoff between security, capacity, imperceptibility and robustness against various signal processing attacks for both audio and speech signals. [ABSTRACT FROM AUTHOR]

In this paper, we use two Fractional-Order Chaotic Systems (FOCS)—one for the sender and one for the receiver—to determine the optimal synchronisation for a secure communication technique. With the help of the Step-By-Step Sliding-Mode Observer (SBS-SMO), this synchronisation is accomplished. An innovative optimisation method, known as the artificial Harris hawks optimisation (HHO), was employed to enhance the observer's performance. This method eliminates the random parameter selection process and instead selects the optimal values for the observer. In a short amount of time, the secret message that could have been in the receiver portion (signal, voice, etc.) was successfully recovered using the proposed scheme. The experimental validation of the numerical results was carried out with the assistance of an Arduino microcontroller and several electronic components. In addition, the findings of the experiments were compared with the theoretical calculations, revealing a satisfactory level of agreement. [ABSTRACT FROM AUTHOR]

The aim of this work is the synthesis of a type-2 fuzzy logic PID controller for DC-DC boost converters. Performances of the proposed controller are evaluated and compared with those of type-1 fuzzy logic PID controller using the same structure and under similar operating conditions. Simulation results showed that the type-2 fuzzy logic PID controller has better performances than those of type-1 fuzzy logic PID controller. [ABSTRACT FROM AUTHOR]

Abstract: In this work, we present a mixed software/hardware implementation of 2-D signals encoder/decoder using dyadic discrete wavelet transform (DWT) based on quadrature mirror filters (QMF); using fast wavelet Mallat's algorithm. This work is designed and compiled on the embedded development kit EDK6.3i, and the synthesis software, ISE6.3i, which is available with Xilinx Virtex-IIV2MB1000 FPGA. Huffman coding scheme is used to encode the wavelet coefficients so that they can be transmitted progressively through an Ethernet TCP/IP based connection. The possible reconfiguration can be exploited to attain higher performance. The design will be integrated with the neutron radiography system that is used with the Es-Salem research reactor. [Copyright &y& Elsevier]

Abstract: Image deblurring is indispensable to many image processing applications. In this paper, we try to improve radiological images degraded during acquisition and processing. An autoregressive moving average (ARMA) model, used for nonlinearly degraded image deconvolution, is identified using a neural network (NN). The NN training is improved using a novel swarm optimization algorithm called Artificial Bees Colony (ABC), inspired from the foraging intelligence of honey bees. The ABC has the advantage of employing fewer control parameters compared to other swarm optimization algorithms. Both estimated image and blur function are identified through this representation. The optimized ARMA-NN model is then implemented on a Xilinx reconfigurable field-programmable gate array (FPGA) using hardware description language: VHDL. This VHDL code is tested on the rapid prototyping platform named ML505 based on a Virtex5-LXT FPGA chip of Xilinx. Simulation results using some test and real images are presented to sustain the applicability of this approach compared to the standard blind image deconvolution (BID) method that maximizes the likelihood using an iterative process. A statistical comparison is concluded based on performance evaluation using seven recent image quality metrics. [Copyright &y& Elsevier]

Image deconvolution is an important problem in image processing. It is an ill-posed inverse problem, so regularization techniques are used to solve this problem by adding constraints to the objective function. Various popular algorithms have been developed to solve such problem. This paper proposes a new approach to the nonlinear neutron degraded images restoration problem which is useful in many images enhancement applications, based on swarm intelligence. We use the particle swarm optimization (PSO) applied for total variation (TV) minimization, instead of the standard Tikhonov regularization method. In this work, we attempt to reconstruct or recover neutron radiography images that have been degraded during acquisition; using some a priori knowledge of the degradation phenomenon. The truncated singular value decomposition (TSVD) method is also considered for image deconvolution in this paper. A comparison between the five methods is conducted, using several images. [ABSTRACT FROM AUTHOR]

In this work, an optimal infinite impulse response (IIR) filter is designed using least Pth norm and new meta‐heuristic optimization algorithm called Crow Search Algorithm (CSA). The two approaches try to get a resolution to the specified problem but use unlike approaches to perform so. Furthermore, the ℓp‐norm is used to design optimum IIR filters. The main motivation of using CSA is its user‐friendly optimization tool for both beginner and professional users. This Algorithm provides a good stability between variety and strength which are mainly controlled by the parameter of awareness probability. Some examples of IIR filter design cases are treated, and a comparison is done. It is revealed that the design objective is successfully attained, and the resultant filter parameters are better using the ℓp‐norm combined with the proposed CSA meta‐heuristic optimization algorithms compared with IIR filter designed using butter synthesis approach in terms of accuracy and robustness. Classical approaches are largely outperformed by CSA for the same filter order. [ABSTRACT FROM AUTHOR]

The strategy of control for high-voltage direct current system on voltage-source converter VSC-HVDC is based on an important element which is PI controller. Because of its simple structure and strong robustness in a wide range of serving conditions, it has been used in the control system in the last few years. Therefore, it is important for the VSC-HVDC system permanent regime to choose proper PI parameters. The use of conventional techniques to find suitable PI parameters creates a number of challenges for the system operators, because it is a difficult process and time consuming. In this paper, a new swarm intelligence algorithm called bacterial foraging optimization is introduced to find the optimal parameters of the PI controller. This approach offers great flexibility for the permanent regime recovery and improves the stability of the VSC-HVDC link compared to conventional techniques. The obtained results are presented to show the effectiveness of the proposed swarm implementation for optimal controller design for VSC-HVDC transmission. MATLAB/Similink simulations are provided to demonstrate the performance of the proposed approach. [ABSTRACT FROM AUTHOR]