We propose a mathematical system capable of exhibiting chaos with a chaotic attractor which is odd symmetrical in the x − y phase plane but even symmetrical in the x − z and y − z phase planes respectively. A hardware implementation of the system is done on a digital FPGA platform for verification. The system is also attractive in the sense that (i) its dynamics are single-parameter controlled and

Binary convolutional neural networks (BCNN) have been proposed in the literature for resource-constrained IoTs nodes and mobile computing devices. Such computing platforms have strict constraints on the power budget, system performance, processing and memory capabilities. Nonetheless, the platforms are still required to efficiently perform classification and matching tasks needed in various

Fractional-order lead/lag compensator realizations, using Operational Transconductance Amplifiers as active blocks, are presented in this paper. Two different types of fractional-order transfer functions, derived from the integer-order lead/lag compensator transfer function, are used to describe the behavior of the fractional-order compensator. Both types are approximated using the Padé

The power-energy performance of supercapacitors is usually visualized by the Ragone plot of (gravimetric or volumetric) energy density vs power density. The energy is commonly computed from E = CV2/2, and the power from P = E/Δt, which assume RCbased models. In this study, we investigate the energy-power profiles of two commercial supercapacitors discharged with three different types of loads: (i)

This paper presents a novel lossless image encryption algorithm based on edge detection and generalized chaotic maps for key generation. Generalized chaotic maps, including the fractional-order, the delayed, and the Double-Humped logistic maps, are used to design the pseudo-random number key generator. The generalization parameters add extra degrees of freedom to the system and increase the

Concentrated Solar Power (CSP) systems have a good potential as a renewable energy candidate that are based on converting the incident solar thermal energy to an electrical energy. In this paper, CSP using spot Fresnel lens instead of traditional lenses is presented to enhance the efficiency of the system, where Silicon Carbide (SiC) is used as a coating material for the receiver of the system due

In this study we quantify and interpret the inherent memory in fractional-order capacitors when subjected to constant current charging/discharging waveforms. This is done via a finite difference approximation of the fractional order rate equation I(t) = Cαdαv(t)/dtα (0 le; α ≤ 1) relating current to voltage in these devices. It is found that as the fractional exponent α decreases, the weight of

A novel non-uniform Kramers–Kronig Transform algorithm for bioimpedance phase extraction is proposed and tested in this work. The algorithm error is studied and compared with a previously proposed phase extraction technique, also based on the Kramers–Kronig transform. Results using simulated datasets and experimental datasets confirm the excellent performance of the algorithm. © 2020, European

This paper presents a practical emulator of a generalised fractional-order model for gene regulation process, in an analog platform. The presented emulator is based on the second-generation current conveyor (CCII) and implemented using AD844 chips. The emulator realises a proposed generalised mathematical model for gene expression. The model sums up three different single models; the constitutive

Convolutional Neural Networks (CNNs) for Artificial Intelligence (AI) algorithms have been widely used in many applications especially for image recognition. However, the growth in CNN-based image recognition applications raised challenge in executing millions of Multiply and Accumulate (MAC) operations in the state-of-The-Art CNNs. Therefore, GPUs, FPGAs, and ASICs are the feasible solutions for