This paper presents the development of a new Matlab mosfetmodel specifically designed for RLC circuits. The key contribution is the formulation of a novel equation that accurately captures the device behavior across subthreshold, above-threshold regions and at threshold point, addressing limitations in existing models. The developed model treats themosfetas a variable resistance element, with the resistance changing dynamically at each instant, enabling the solution of differential equations governing the RLC circuit. Curve fitting and refinement were conducted based on experimental results, leading to a close match between the simulations and experimental data. The model was tested with triangle, sinusoidal and quadrilateral gate voltages, and the simulation results show good match with the experimental data, demonstrating the model’s accuracy. It provides a straightforward way to predict performance, making it easier to refine and optimize the design gate voltage before physical implementation. This work provides a solid foundation formosfetmodeling in oscillatory RLC circuits, which can be applied to a wide range of power electronics applications.

High-voltage pulse generators are useful in many applications such as transient surge simulators, electric fence energizers, and transcranial magnetic stimulation (TMS) systems. Traditionally they are based on a high-voltage DC power supply with or without voltage multipliers for raising the voltage to several thousand volts. In contrast to these complex and costly approaches, we use a pre-charged supercapacitor followed by a step-up transformer and associated output circuitry to develop an inexpensive and flexible high-voltage pulse generator for applications in transcranial magnetic stimulation. Our new approach is to use the high-power delivery capability of commercial supercapacitors. In this work, we explore the advantages of different waveforms applied to the MOSFET associated with the secondary stage of the circuit topology and how they affect the final pulse shape.

High power pulse generators with variable parameters are helpful in many applications in the industrial and medical fields. The traditional approach to design these pulse generators is to start with a high voltage DC power supply, energy storage capacitor, and a wave shaping circuit. However, building a high-voltage DC power supply itself is a complex task and it ends up in a complicated circuit with several high-voltage components hence adding to the total cost. This paper presents a unique new approach to designing a supercapacitor-based high-voltage pulse generator with a lower number of components and simple two-winding transformer. First experimental circuit developed based on this new approach is presented here with variable pulse generator capable of several hundred volts peak voltage with loop current capability of several hundred amperes.

Relationships between spiking-neuron and rate-based approaches to the dynamics of neural assemblies are explored by analyzing a model system that can be treated by both methods, with the rate-based method further averaged over multiple neurons to give a neural-field approach. The system consists of a chain of neurons, each with simple spiking dynamics that has a known rate-based equivalent. The neurons are linked by propagating activity that is described in terms of a spatial interaction strength with temporal delays that reflect distances between neurons; feedback via a separate delay loop is also included because such loops also exist in real brains. These interactions are described using a spatiotemporal coupling function that can carry either spikes or rates to provide coupling between neurons. Numerical simulation of corresponding spike- and rate-based methods with these compatible couplings then allows direct comparison between the dynamics arising from these approaches. The rate-based dynamics can reproduce two different forms of oscillation that are present in the spike-based model: spiking rates of individual neurons and network-induced modulations of spiking rate that occur if network interactions are sufficiently strong. Depending on conditions either mode of oscillation can dominate the spike-based dynamics and in some situations, particularly when the ratio of the frequencies of these two modes is integer or half-integer, the two can both be present and interact with each other.