Abstract
Development time and accuracy are measures that need to be taken into account when devising device models for a new technology. If complex circuits need to be designed immediately, then it is very important to reduce the time taken to realize the model. Solely based on data measurements, artificial neural networks (ANNs) modeling methodologies are capable of capturing small and large signal behavior of the transistor, with good accuracy, thus becoming excellent alternatives to more strenuous modeling approaches, such as physical and semi-empirical. This paper then addresses a static modeling methodology for amorphous Gallium-Indium-Zinc-Oxide - Thin Film Transistor (a-GIZO TFT), with different ANNs, namely: multilayer perceptron (MLP), radial basis functions (RBF) and least squares-support vector machine (LS-SVM). The modeling performance is validated by comparing the model outcome with measured data extracted from a real device. In case of a single transistor modeling and under the same training conditions, all the ANN approaches revealed a very good level of accuracy for large- and small-signal parameters (g(m) and g(d)), both in linear and saturation regions. However, in comparison to RBF and LS-SVM, the MLP achieves a very acceptable degree of accuracy with lesser complexity. The impact on simulation time is strongly related with model complexity, revealing that MLP is the most suitable approach for circuit simulations among the three ANNs. Accordingly, MLP is then extended for multiple TFTs with different aspect ratios and the network implemented in Verilog-A to be used with electric simulators. Further, a simple circuit (inverter) is simulated from the developed model and then the simulation outcome is validated with the fabricated circuit response.

Abstract
In wireless power transfer systems, if the driver is not capable of dynamically adapt its own switching frequency, small environmental changes or even slight deviations in circuit parameters may prevent the complete system from working properly when the optimal resonance frequency moves towards new values. In this paper, we propose an adaptive system suitable for underwater wireless applications in sea water. The output voltage is regulated using the wireless power link, avoiding the need for additional wireless interfaces. Our complete system includes the power driver, coupling coils, rectifier, and two micro-controllers. The regulation is accomplished by digital load modulation, observable at the input by means of current sensing at the power supply. Experimental results demonstrate a class-D driver with a series-series resonant topology working in saline water, delivering power between 1.6 and 2.4 W. The regulated voltage is 7.5 V with error less than 7.2 % in the load range of 30 to 37 Omega and 6 to 10 V power supply variation. The switching frequency is adjusted within the range of 7 kHz deviation (-7%).

Abstract
In this work we propose a method for maximization of the efficiency of an underwater wireless power transfer system that has to cope with load changes, quality factor and coupling coefficient deviations. By means of 3D electromagnetic simulation and numerical computation, parameter analysis is accomplished using different compensation methods, namely series-series, series-parallel and parallel-parallel. Moreover, a linear load profile is assessed as a proof of concept applicable to more complex load behaviours. For this linear load variation a maximum measured average efficiency of 82% was obtained throughout the entire battery state of charge. Electronics and full system considerations are also presented. Finally, a good agreement between theoretical predictions of the proposed method, simulation assessment and measurement results was verified.

Abstract
The work reported in this paper introduces a periodic switching technique applied to continuous-time filters, whose outcome is an equivalent filter with scaled time-constants. The principle behind the method is based on a procedure that extends the integration time by periodically interrupting the normal integration of the filter. The net result is an up scaling of the time constant, inversely proportional to the switching duty-cycle. This is particularly suitable for reducing the area occupied by passive devices in integrated circuits, as well as to accurately calibrate the filter dynamics. Previous works have been following this concept in an entirely continuous-time perspective, either focusing on specific circuits or using approximations to provide an extended analysis. This paper includes input/output sampling to derive a closed-form representation for the scaling technique herein coined as 'Filter & Hold' (F&H). A detailed mathematical analysis is described, demonstrating that the F&H concept represents an exact filtering solution. Simulation results and experimental measurements are provided to further validate the theoretical analysis for an F&H vector-filter prototype. Copyright (C) 2014 John Wiley & Sons, Ltd.

Abstract
This work presents a new topology for the matching networks of an underwater wireless power transfer system. A class-D driver is used in resonance at fundamental and third harmonic frequencies. The double resonance helps reducing the reverse voltage stress at the diode rectifier. We present the analytical derivation of the proposed network and demonstrate the design procedure with an example. We also show that additional degrees of freedom can be acquired with the proposed topology, which improves the design space for time-varying operation conditions of our application, such as the load changing when a battery is being recharged. The performance of our topology is compared to most conventional approaches, such as the series-series and series-parallel networks, revealing a good compromise between power delivery and efficiency across a wide load range.

Abstract
The integrate-and-fire model of a biological neuron is an amplitude to time encoding in the spacing between action potentials (spikes). In principle, this encoding can be used to modulate signals in an Impulse Radio Ultra Wide-Band (IRUWB) transmitter suitable for Wireless Sensor Networks (WSN). This paper presents a system level study on power efficiency using MATLAB/ Simulink to evaluate the required energy for an IR-UWB Transmitter using integrate-and-fire encoding technique. Also, a simple but clear comparison with common systems utilizing Nyquist rate Analog-to-Digital Converters (ADC) is presented. This study has been carried out on a band-limited random Gaussian signal and the results show that IR-IF transmitter consumes roughly seven times less energy than a digital UWB transmitter; moreover, in the proposed architecture the need for power hungry ADC is relaxed.