Inernet Tool for Electronic Circuit Analysis

This book is concerned with circuit simulation using National Instruments Multisim. It focuses on the use and comprehension of the working techniques for electrical and electronic circuit simulation. The first chapters are devoted to basic circuit analysis. It starts by describing in detail how to perform a DC analysis using only resistors and independent and controlled sources. Then, it introduces capacitors and inductors to make a transient analysis. In the case of transient analysis, it is possible to have an initial condition either in the capacitor voltage or in the inductor current, or both. Fourier analysis is discussed in the context of transient analysis. Next, we make a treatment of AC analysis to simulate the frequency response of a circuit. Then, we introduce diodes, transistors, and circuits composed by them and perform DC, transient, and AC analyses. The book ends with simulation of digital circuits. A practical approach is followed through the chapters, using step-by-step examples to introduce new Multisim circuit elements, tools, analyses, and virtual instruments for measurement. The examples are clearly commented and illustrated. The different tools available on Multisim are used when appropriate so readers learn which analyses are available to them. This is part of the learning outcomes that should result after each set of end-of-chapter exercises is worked out. Table of Contents: Introduction to Circuit Simulation / Resistive Circuits / Time Domain Analysis -- Transient Analysis / Frequency Domain Analysis -- AC Analysis / Semiconductor Devices / Digital Circuits

SummaryThe approximation technology of analogue circuit functions is crucial to the computer‐aided simulation, analysis, and design automation of electronic circuits. Chebyshev polynomials and various differential equations are proposed in this paper to approximate the functions of linear time‐invariant circuits. The coefficient calculation methods of the Chebyshev expansion and the differential equation matrices are thoroughly deduced, and the construction methods employed in the functions and the actual time mapping of the linear time‐invariant circuits are presented in this paper. An example of an analogue filter verifies the effectiveness and accuracy of the proposed approximation algorithm and elaborates on the selection process of the order number and the time step length of the Chebyshev expansion according to the demanded truncation error.

Thermal analysis of layered electronic circuits with Green's functions

We propose a model of an equivalent electrical circuit specifically designed for a ferrite inductor excited by a nonsinusoidal waveform valid for use in an electronic circuit simulator. We estimate the model parameters by means of Finite Elements in 2-D which leads to significant computational advantages over the 3-D model. We carry out the validation of the procedure for an RM14/I core by comparing the experimental and simulated output waveforms obtained at different frequencies and levels of excitation from the linear to the saturation regions. In addition, we consider the effect of power losses in the core.

A hierarchical symbolic analyzer (SAGA2) for the analysis of electronic circuits is presented. SAGA2 analyzes lumped, linear, or linearized (small-signal) circuits in the S- and Z-domain. For large circuits, a hierarchical two-port method is used that is two to three order faster than that without using the hierarchical method. Also, the memory used is dramatically reduced.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Differential-algebraic equations (DAEs) provide an essential tool for system modeling and analysis within different fields of applied sciences and engineering. This book addresses modeling issues and analytical properties of DAEs, together with some applications in electrical circuit theory. Beginning with elementary aspects, the author succeeds in providing a self-contained and comprehensive presentation of several advanced topics in DAE theory, such as the full characterization of linear time-varying equations via projector methods or the geometric reduction of nonlinear systems.Recent results on singularities are extensively discussed. The book also addresses in detail differential-algebraic models of electrical and electronic circuits, including index characterizations and qualitative aspects of circuit dynamics. In particular, the reader will find a thorough discussion of the state/semistate dichotomy in circuit modeling. The state formulation problem, which has attracted much attention in the engineering literature, is cleverly tackled here as a reduction problem on semistate models.

Introduction to Linear Circuit Analysis and Modelling

With the rapid development of science and technology and social economy, neural network, as the main research direction of modern intelligent system, has played a positive role in medical devices, intelligent robots, automatic control and other fields. In this paper, when studying the neural network as the core of analog electronic circuit model, MOS transistor is used to build the corresponding basic circuit model, and the relevant algorithm is introduced and analyzed. Pspice is chosen as the development platform. Compared with digital circuit, analog circuit can be completed with fewer components, while MOS transistor can facilitate integrated circuit, and the neural network algorithm code needs to be written in Matlab software simulation. The final results show that the neural network as the core of the analog electronic circuit model can not only obtain more algorithm functions, but also improve the integration of neural network, so it belongs to the main direction of modern integrated circuit innovation development.

In recent years, reduced-order modelling techniques based on Krylov-subspace iterations, especially the Lanczos algorithm and the Arnoldi process, have become popular tools for tackling the large-scale time-invariant linear dynamical systems that arise in the simulation of electronic circuits. This paper reviews the main ideas of reduced-order modelling techniques based on Krylov subspaces and describes some applications of reduced-order modelling in circuit simulation.

Analysis and design of analogue electronic circuits using DPI methods — Part 2: circuits containing different types of active devices Circuits with combinations of bipolar and field effect transistors as active devices are studied. It is shown that dealing with such problems poses no additional difficulties. An example is given.

A new finite element technique that allows nonlinear time domain analysis of power electronic circuits containing magnetic components is presented. The new technique is shown to compute the same voltage waveform in a nonlinear RLC circuit as previously published circuit techniques. The new technique is demonstrated for a circuit containing an inductor with a nonlinear B-H curve, finite conductivity and a given geometry including air gaps. >

Computationally efficient large-change statistical analysis of linear electronic circuits

A new simulation technique for analysis of power electronics circuits is presented. It is based on using the Chebyshev polynomial to derive an adaptive stepwise quadratic state-space model for each piecewise-linear circuit topology, where the state-space equation sets are integrated with modified nodal formulations (MNF). The key feature of this algorithm is to determine an optimum step size for the model to achieve desired accuracy. The switching instants are directly calculated by solving simple quadratic equations. No prior knowledge of the circuit operations is required. The theoretical predictions are verified with the results obtained in the available literature.

This research work reports a double-wing chaotic system with a line of equilibrium points and constructs an electronic circuit via MultiSIM for practical implementation. Explicitly, the new chaotic system has a total of six terms with two quadratic nonlinearities and absolute function nonlinearity. Using the phase plots in MATLAB, we demonstrate that the new chaotic system has double-wing chaotic attractor. We describe the Lyapunov exponents and the Kaplan-Yorke fractal dimension of the new chaotic system. A novel feature of the new chaotic system is that the system has rest points located on the z-axis as well as two rest points not on the z-axis. Thus, the new system has infinite number of rest points and hidden attractor. We also exhibit that the new double-wing chaotic system has multi-stability and we illustrate the coexistence of attractors for two different sets of initial conditions. Some interesting dynamical properties such as offset boosting are also presented. Finally, we build an electronic circuit of the new chaotic system and show that the theoretical model has practical feasibility for implementation.

Tensor decomposition methods are widely used for solving high-dimensional and multi-dimensional problems. These approaches have a huge potential for reducing computational costs in the simulation of electronic circuits and in the CAD systems for electronics. Simulation of modern radio-frequency (RF) circuits, especially for RF integrated circuits, is one of the areas of extensive scientific research and development. The main problem of analysis methods for circuit design of RF electronics is the significant computational costs associated with the high dimensions to be solved. This paper shows that the computational costs of circuit design are largely determined by the costs of solving a system of linear algebraic equations (SLAE). The problems of the solving of SLAE are indicated in the paper. Further development of methods for solving and reducing computational costs requires the use of new approaches, one of which is proposed in this paper. The article presents the developed algorithm for converting a second-order matrix into a higher-order tensor. In this paper algorithms and software tools for tensor decompositions, as well as methods for solving SLAE in the representation of equations in tensor format are investigated. The results of numerical experiments and the results of comparison with traditional methods are presented.