Abstract-This paper deals with modeling and simulation of a new family of two-terminal devices fabricated with vanadium dioxide material. Such devices allow realization of very compact relaxation nano-oscillators that can be connected electronically to form arrays of coupled oscillators. Challenging applications of oscillator arrays include the realization of multi-phase signal generators and massively parallel brain-inspired neurocomputing. In the paper, a circuit-level model of the vanadium dioxide device is provided which enables extensive electrical simulations of oscillator systems built on the device. The proposed model is exploited to explain the dynamics of vanadium dioxide relaxation oscillators as well as to accomplish a robust parameter design. Applications to the realization of voltage-controlled oscillators and of multi-phase oscillator arrays are illustrated.

In this paper, a novel analysis method based on Wave Digital (WD) principles is presented. The method is employed for modeling and efficiently simulating large PhotoVoltaic (PV) arrays under partial shading conditions. The WD method allows rapid exploration of the current-voltage curve at the load of the PV array, given: the irradiation pattern, the nonlinear PV unit model (e.g. exponential junction model with bypass diode) and the corresponding parameters. The Maximum Power Point can therefore easily be deduced. The main features of the proposed method are the use of a scattering matrix that is able to incorporate any PV array topology and the adoption of independent one-dimensional nonlinear solvers to handle the constitutive equations of PV units. It is shown that the WD method can be considered as an iterative relaxation method that always converges to the PV array solution. Rigorous proof of convergence and results about the speed of convergence are provided. Compared to standard Spice-like simulators, the WD method results to be 35 times faster for PV arrays made of some thousands elements. This paves the way to possible implementations of the method in specialized hardware/software for the real time control and optimization of complex PV plants.

Brain-inspired arrays of parallel processing oscillators represent an intriguing alternative to traditional computational methods for data analysis and recognition. This alternative is now becoming more concrete thanks to the advent of emerging oscillators fabrication technologies providing high density packaging and low power consumption. One challenging issue related to oscillator arrays is the large number of system parameters and the lack of efficient computational techniques for array simulation and performance verification. This paper provides a realistic phase-domain modeling and simulation methodology of oscillator arrays which is able to account for the relevant device nonidealities. The model is employed to investigate the associative memory performance of arrays composed of resonant LC oscillators

In this paper we consider the problem of approximating the large discretized thermal network that models the heat conduction phenomenon in an electrical system by means of models of reduced state-space dimensions. To this aim we present an efficient and numerically stable Arnoldi type algorithm by which a multi-point moment matching approximant of the discretized thermal network is obtained and we apply it to the electro-thermal analysis of an operational transconductance amplifier.

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Process variations are a major concern in today's chip design since they can significantly degrade chip performance. To predict such degradation, existing circuit and MEMS simulators rely on Monte Carlo algorithms, which are typically too slow. Therefore, novel fast stochastic simulators are highly desired. This paper first reviews our recently developed stochastic testing simulator that can achieve speedup factors of hundreds to thousands over Monte Carlo. Then, we develop a fast hierarchical stochastic spectral simulator to simulate a complex circuit or system consisting of several blocks. We further present a fast simulation approach based on anchored ANOVA (analysis of variance) for some design problems with many process variations. This approach can reduce the simulation cost and can identify which variation sources have strong impacts on the circuit's performance. The simulation results of some circuit and MEMS examples are reported to show the effectiveness of our simulator

There is a growing interest in Virtual Analog modeling algorithms for musical audio processing designed in the Wave Digital (WD) domain. Such algorithms typically employ a discretization strategy based on the trapezoidal rule with fixed sampling step, though this is not the only option. In fact, alternative discretization strategies (possibly with an adaptive sampling step) can be quite advantageous, particularly when dealing with nonlinear systems characterized by stiff equations. In this article, we propose a unified approach for modeling capacitors and inductors in the WD domain using generic linear multi-step discretization methods with variable time-step size, and provide generalized adaptation conditions. We also show that the proposed approach for implementing dynamic (energystoring) elements in the WD domain is particularly suitable to be combined with a recently developed technique for efficiently solving a class of circuits with multiple one-port nonlinearities, called Scattering Iterative Method. Finally, as examples of application, we develop WD models for a Van Der Pol oscillator and a dynamic diode-based ring modulator, which use different discretization methods.

Abstract-This brief paper proposes an uncertainty quantification method for the periodic steady-state (PSS) analysis with both Gaussian and non-Gaussian variations. Our stochastic testing formulation for the PSS problem provides superior efficiency over both Monte Carlo methods and existing spectral methods. The numerical implementation of a stochastic shooting Newton solver is presented for both forced and autonomous circuits. Simulation results on some analog/RF circuits are reported to show the effectiveness of our proposed algorithms.