A Novel Algebraic Technique for the Construction of Strong Substitution Box

Magnetic induction applications mostly rely on resonance for inducing maximum magnetic fields to system loads and hence for each resonant frequency dedicated circuits are required. Unfortunately, the frequency responses of such inductive systems manifest several peaks (frequency splitting) when their coupling coefficients are equal to or larger than critical coupling. Such frequency responses with several peaks are detrimental when the objective is to transfer maximum energy. Frequency splitting between inductive coils have been seen to date as detrimental to wireless power transfer and inductive communication systems. In this paper it is demonstrated that frequency splitting is a welcome phenomenon with advantage in the design of inductive filter banks and multi-frequency inductive systems. The centre frequencies of the filter banks result from split bands of inductive systems. This phenomenon is applied in conjunction with an innovative recursive algorithm to design inductive filter banks. The filters straddle both sides of the resonant frequency position and can be resolved individually.     

Maximum likelihood-based adaptive differential evolution identification algorithm for multivariable systems in the state-space form

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms.     

Recursive least squares estimation methods for a class of nonlinear systems based on non-uniform sampling

Many dynamic processes in practice have nonlinear characteristics and must be described by using nonlinear models. It remains to be a challenging problem to build the models of such nonlinear systems and to estimate their parameters. This article studies the parameter estimation problem for a class of Hammerstein-Wiener nonlinear systems based on non-uniform sampling. By means of the auxiliary model identification idea, an auxiliary model-based recursive least squares algorithm is derived for the systems. In order to enhance the computational efficiency, an auxiliary model-based hierarchical least squares algorithm is proposed by utilizing the hierarchical identification principle. The simulation results confirm the effectiveness of the proposed algorithms.     

An Efficient Digital Confidentiality Scheme Based on Commutative Chaotic Polynomial

Multimedia Tools and Applications - One of the most critical aspects of this technologically progressive era is the propagation of information through an unsecured communication channel. The...     

A hybrid composite of rGO/TiO2 as a double layer electrode with improved capacitance performance

Reduced graphene oxide (rGO) has unique properties that can revolutionize the performance of the functional devices. rGO hybrids can be designed with transition metal oxides for improved energy storage applications. Herein, a hybrid composite of conductive rGO with titanium dioxide, designed by a simple hydrothermal method, is reported to demonstrate a high double layer capacitance in aqueous electrolyte systems. The mesoporous structure of the composite provides short ion diffusion pathways and the resultant capacitance of the material is 334 F g⁻¹ with ~77% capacitance retention after 7000 charge-discharge cycles.     

A novel efficient image encryption algorithm based on affine transformation combine with linear fractional transformation

Multidimensional Systems and Signal Processing - Algebraic structures and their hardware–software implementation gain considerable attention in the field of information security and coding...     

Features of Cattaneo‐Christov heat flux model for Stagnation point flow of a Jeffrey fluid impinging over a stretching sheet: A numerical study

The present work focuses on a two‐dimensional steady incompressible stagnation point flow of a Jeffery fluid over a stretching sheet. The Cattaneo‐Christov heat flux model is incorporated into this study. Simulation is conducted via the Runge‐Kutta fourth‐order cum shooting method for the transformed system of nonlinear equations. The influence of the governing parameters on the dimensionless velocity, temperature, skin friction, streamlines, and isotherms is incorporated. A significant outcome of the current investigation is that an increase in the relaxation time parameter uplifts temperature; however, a gradual decrease is observed in the velocity field. Another important outcome of the present analysis is that the momentum boundary layer augments due to an increase in the Deborah number; however, a decrease is observed in the temperature. Furthermore, it is also observed that the skin friction coefficient escalates with an increase in the relaxation time parameter for the assisting flow, but a reverse trend is observed for the opposing flow.