Emulation of Circuits under Test Using Low-Cost Embedded Platforms

Electrical engineering education requires the development of the specific ability and skills to address the design and assembly of practical electronic circuits, as well as the use of advanced electronic instrumentation. However, for electronic instrumentation courses or any other related specialty that pursues to gain expertise testing a physical system, the circuit assembly process itself can represent a bottleneck in a practical session. The time dedicated to the circuit assembly is subtracted both to the measurements and the final decision-making time. Therefore, the student's practical experience is limited. This article presents a reconfigurable physical system based on the Arduino (TM) shield pin-out, which (after specific programming) can virtually behave as a device under test to carry out measurement procedures on it, emulating any system or process. Although it has been mainly oriented to the Arduino boards, it is possible to add different control devices with a connector compatible. The user does not need to assemble any circuit. Our approach does not only pursue the correct instrument handling as a goal, but it also immerses the student in the context of the functional theory of the proposed circuit under test. Consequently, the same emulation platform can be utilized for other techno-scientific specialties, such as electrical engineering, automatic control systems or physics courses. Besides that, it is a compact product that can be adapted to the needs of any teaching institution.This work was performed as an innovation and teaching improvement project and supported by grant SOL-201700083174-TRA from Vicerrectorado de Recursos Docentes y de la Comunicacion, University of Cadiz

Analytical Solutions to Minimum-Norm Problems

For G is an element of Rmxn and g is an element of Rm, the minimization min parallel to G psi-g parallel to 2, with psi is an element of Rn, is known as the Tykhonov regularization. We transport the Tykhonov regularization to an infinite-dimensional setting, that is min parallel to T(h)-k parallel to, where T:H -> K is a continuous linear operator between Hilbert spaces H,K and h is an element of H,k is an element of K. In order to avoid an unbounded set of solutions for the Tykhonov regularization, we transform the infinite-dimensional Tykhonov regularization into a multiobjective optimization problem: min parallel to T(h)-k parallel to andmin parallel to h parallel to. We call it bounded Tykhonov regularization. A Pareto-optimal solution of the bounded Tykhonov regularization is found. Finally, the bounded Tykhonov regularization is modified to introduce the precise Tykhonov regularization: min parallel to T(h)-k parallel to with parallel to h parallel to=alpha. The precise Tykhonov regularization is also optimally solved. All of these mathematical solutions are optimal for the design of Magnetic Resonance Imaging (MRI) coils

Pareto Optimality for Multioptimization of Continuous Linear Operators

This manuscript determines the set of Pareto optimal solutions of certain multiobjective-optimization problems involving continuous linear operators defined on Banach spaces and Hilbert spaces. These multioptimization problems typically arise in engineering. In order to accomplish our goals, we first characterize, in an abstract setting, the set of Pareto optimal solutions of any multiobjective optimization problem. We then provide sufficient topological conditions to ensure the existence of Pareto optimal solutions. Next, we determine the Pareto optimal solutions of convex max-min problems involving continuous linear operators defined on Banach spaces. We prove that the set of Pareto optimal solutions of a convex max-min of form max parallel to T(x)parallel to, min parallel to x parallel to coincides with the set of multiples of supporting vectors of T. Lastly, we apply this result to convex max-min problems in the Hilbert space setting, which also applies to convex max-min problems that arise in the design of truly optimal coils in engineering

Performance of parallel FDTD method for shared- and distributed-memory architectures: Application tobioelectromagnetics

This work provides an in-depth computational performance study of the parallel finite-difference time-domain (FDTD) method. The parallelization is done at various levels including: shared- (OpenMP) and distributed- (MPI) memory paradigms and vectorization on three different architectures: Intel's Knights Landing, Skylake and ARM's Cavium ThunderX2. This study contributes to prove, in a systematic manner, the well-established claim within the Computational Electromagnetic community, that the main factor limiting FDTD performance, in realistic problems, is the memory bandwidth. Consequently a memory bandwidth threshold can be assessed depending on the problem size in order to attain optimal performance. Finally, the results of this study have been used to optimize the workload balancing of simulation of a bioelectromagnetic problem consisting in the exposure of a human model to a reverberation chamber-like environment

Exact Solutions to the Maxmin Problem max parallel to Ax parallel to Subject to parallel to Bx parallel to <= 1

In this manuscript we provide an exact solution to the maxmin problem max parallel to Ax parallel to subject to parallel to Bx parallel to <= 1, where A and B are real matrices. This problem comes from a remodeling of max parallel to Ax parallel to subject to min parallel to Bx parallel to, because the latter problem has no solution. Our mathematical method comes from the Abstract Operator Theory, whose strong machinery allows us to reduce the first problem to max parallel to Cx parallel to subject to parallel to x parallel to <= 1, which can be solved exactly by relying on supporting vectors. Finally, as appendices, we provide two applications of our solution: first, we construct a truly optimal minimum stored-energy Transcranian Magnetic Stimulation (TMS) coil, and second, we find an optimal geolocation involving statistical variablesSpanish Ministry of Science, Innovation and Universities - FEDE

Analytical Solutions to Minimum-Norm Problems

For G&isin;Rm&times;n and g&isin;Rm, the minimization min&#8741;G&psi;&minus;g&#8741;2, with &psi;&isin;Rn, is known as the Tykhonov regularization. We transport the Tykhonov regularization to an infinite-dimensional setting, that is min&#8741;T(h)&minus;k&#8741;, where T:H&rarr;K is a continuous linear operator between Hilbert spaces H,K and h&isin;H,k&isin;K. In order to avoid an unbounded set of solutions for the Tykhonov regularization, we transform the infinite-dimensional Tykhonov regularization into a multiobjective optimization problem: min&#8741;T(h)&minus;k&#8741;andmin&#8741;h&#8741;. We call it bounded Tykhonov regularization. A Pareto-optimal solution of the bounded Tykhonov regularization is found. Finally, the bounded Tykhonov regularization is modified to introduce the precise Tykhonov regularization: min&#8741;T(h)&minus;k&#8741;with&#8741;h&#8741;=&alpha;. The precise Tykhonov regularization is also optimally solved. All of these mathematical solutions are optimal for the design of Magnetic Resonance Imaging (MRI) coils

An Embedded Sensor Node for the Surveillance of Power Quality

The energy supply of office buildings and smart homes is a key issue in the global energy system. The growing use of microelectronics-based technology achieves new devices for a more comfortable life and wider use of electronic office equipment. On the one hand, these applications incorporate more and more sensitive electronic devices which are potentially affected by any external electrical transient. On the other hand, the existing electrical loads, which generally use electronic power systems (such as different types of battery chargers, ballasts, inverters, switching power supplies, etc.), generate different kinds of transients in their own electrical internal network. Moreover, improvements in the information of the state of the mains alternating current (AC) power line allows risk evaluation of any disturbance caused to permanently connected electronic equipment, such as computers, appliances, home security systems, phones, TVs, etc. For this reason, it is nowadays more important to introduce monitoring solutions into the electrical network to measure the level of power quality so that it can protect itself when necessary. This article describes a small and compact detector using a low-cost microcontroller and a very simple direct acquiring circuit. In addition; it analyzes different methods to implement various power quality (PQ) surveillance algorithms that can be implemented in this proposed minimum hardware platform. Hence; it is possible to achieve cheap and low-power monitoring devices that can become nodes of a wireless sensor network (WSN). The work shows that using a small computational effort; reasonable execution speed; and acceptable reliability; this solution can be used to detect a variety of large disturbance phenomena and spread the respective failure report through a 433 MHz or 2.4 GHz radio transmitter. Therefore, this work can easily be extended to the Internet of Things (IoT) paradigm. Simultaneously, a software application (PulsAC) has been developed to monitor the microcontroller&#8217;s real-time progress and detection capability. Moreover, this high-level code (C++ language), allows us to test and debug the different utilized algorithms that will be later run by the microcontroller unit. These tests have been performed with real signals introduced by a function generator and superimposed on the true AC sine wav