5,440 research outputs found

    Symbolic analysis tools-the state of the art

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    This paper reviews the main last generation symbolic analyzers, comparing them in terms of functionality, pointing out also their shortcomings. The state of the art in this field is also studied, pointing out directions for future research

    An error-controlled methodology for approximate hierarchical symbolic analysis

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    Limitations of existing approaches for symbolic analysis of large analog circuits are discussed. To address their solution, a new methodology for hierarchical symbolic analysis is introduced. The combination of a hierarchical modeling technique and approximation strategies, comprising circuit reduction, graph-based symbolic solution of circuit equations and matrix-based error control, provides optimum results in terms of speech and quality of results.European Commission ESPRIT 21812Comisión Interministerial de Ciencia y Tecnología TIC97-058

    Error control in simplification before generation algorithms for symbolic analysis of large analogue circuits

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    Circuit reduction is a fundamental first step in addressing the symbolic analysis of large analogue circuits. A new algorithm for simplification before generation is presented which is very efficient in terms of speed and the amount of circuit reduction, and solves the accuracy problems of previously reported approaches

    Symbolic analysis of large analog integrated circuits by approximation during expression generation

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    A novel algorithm is presented that generates approximate symbolic expressions for small-signal characteristics of large analog integrated circuits. The method is based upon the approximation of an expression while it is being computed. The CPU time and memory requirements are reduced drastically with regard to previous approaches, as only those terms are calculated which will remain in the final expression. As a consequence, the maximum circuit size amenable to symbolic analysis has largely increased. The simplification procedure explicitly takes into account variation ranges of the symbolic parameters to avoid inaccuracies of conventional approaches which use a single value. The new approach is also able to take into account mismatches between the symbolic parameters

    Automated Observability Investigation of Analog Electronic Circuits using SPICE

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    In the present paper, a computer-aided approach to fault observability investigation of linear analog circuits is developed. The method is based on sensitivity investigation of the test characteristics in the frequency domain. The test frequencies are selected maximizing the sensitivity of the magnitude of the test characteristics. Applying postprocessing of the simulation results using macrodefinitions in the graphical analyzer Probe, a fault observability investigation of the circuit is performed. A number of sensitivity measures are defined in Probe for observability investigation of multiple faults using pre-defined macrodefinitions. The sensitivity of S-parameters is obtained in order to investigate the fault observability at RF

    Systematic Comparison of HF CMOS Transconductors

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    Transconductors are commonly used as active elements in high-frequency (HF) filters, amplifiers, mixers, and oscillators. This paper reviews transconductor design by focusing on the V-I kernel that determines the key transconductor properties. Based on bandwidth considerations, simple V-I kernels with few or no internal nodes are preferred. In a systematic way, virtually all simple kernels published in literature are generated. This is done in two steps: 1) basic 3-terminal transconductors are covered and 2) then five different techniques to combine two of them in a composite V-I kernel. In order to compare transconductors in a fair way, a normalized signal-to-noise ratio (NSNR) is defined. The basic V-I kernels and the five classes of composite V-I kernels are then compared, leading to insight in the key mechanisms that affect NSNR. Symbolic equations are derived to estimate NSNR, while simulations with more advanced MOSFET models verify the results. The results show a strong tradeoff between NSNR and transconductance tuning range. Resistively generated MOSFETs render the best NSNR results and are robust for future technology developments

    Tensor Computation: A New Framework for High-Dimensional Problems in EDA

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    Many critical EDA problems suffer from the curse of dimensionality, i.e. the very fast-scaling computational burden produced by large number of parameters and/or unknown variables. This phenomenon may be caused by multiple spatial or temporal factors (e.g. 3-D field solvers discretizations and multi-rate circuit simulation), nonlinearity of devices and circuits, large number of design or optimization parameters (e.g. full-chip routing/placement and circuit sizing), or extensive process variations (e.g. variability/reliability analysis and design for manufacturability). The computational challenges generated by such high dimensional problems are generally hard to handle efficiently with traditional EDA core algorithms that are based on matrix and vector computation. This paper presents "tensor computation" as an alternative general framework for the development of efficient EDA algorithms and tools. A tensor is a high-dimensional generalization of a matrix and a vector, and is a natural choice for both storing and solving efficiently high-dimensional EDA problems. This paper gives a basic tutorial on tensors, demonstrates some recent examples of EDA applications (e.g., nonlinear circuit modeling and high-dimensional uncertainty quantification), and suggests further open EDA problems where the use of tensor computation could be of advantage.Comment: 14 figures. Accepted by IEEE Trans. CAD of Integrated Circuits and System
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