Symbolic behavioral model generation of nonlinear analog circuits

Borchers, C.

doi:10.1109/82.728849

Cited by 32 publications

(10 citation statements)

References 30 publications

(29 reference statements)

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“…• Symbolic behavioural models for the AC behaviour of linear and slightly non-linear blocks [4,30], for instance in the case of ampliÿers, active resistances, etc.…”

Section: Modelling Methodsmentioning

confidence: 99%

A behavioural modelling technique for visual microprocessor mixed‐signal VLSI chips

Földesy

Rodríguez-Vázquez

2002

Circuit Theory & Apps

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SUMMARYThis paper describes procedures to build custom-tailored behavioural models of cellular neural networks (CNNs), and acompanion tool to run these models. The main property of the CNNs is the emerging behaviour, i.e. new phenomena arise from the interactions of thousands of identical cells. The existence of these phenomena need is to be checked during the design phase, which requires a full network simulation and therefore constitutes a very time-consuming step of circuit veriÿcation. To solve this task as a modelling problem, we introduce a new behavioural model optimization technique. Starting from a user-deÿned set of block models, the proposed framework produces an optimized selection which is used to build up a full-chip model. The optimization goal is the minimization of the simulation CPU time and the maximization of the time domain precision. A dedicated environment has been developed for e cient numerical simulation; this environment is brie y described in the paper. Two case studies are also presented to demonstrate the e ectivity of the technique.

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“…• Symbolic behavioural models for the AC behaviour of linear and slightly non-linear blocks [4,30], for instance in the case of ampliÿers, active resistances, etc.…”

Section: Modelling Methodsmentioning

confidence: 99%

A behavioural modelling technique for visual microprocessor mixed‐signal VLSI chips

Földesy

Rodríguez-Vázquez

2002

Circuit Theory & Apps

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“…There exists some work on symbolic model generation for linear time varying systems also [Vanassche et al 2002]. Symbolic behavioral model generation for nonlinear circuits is presented in [Borchers 1998]. …”

Section: Behavioral Modeling Approaches and Parameter Estimation Techmentioning

confidence: 99%

Chassis

Ain

Pal

Dasgupta

et al. 2011

ACM Trans. Des. Autom. Electron. Syst.

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Power Management Units (PMUs) are large integrated circuits consisting of many predesigned mixed-signal components. PMU integration poses a serious verification problem considering the size of the integrated circuit and the complexity of analog simulation. In this article we present an approach for automatic generation of behavioral models for PMU components from top-down skeleton models, fitted with parameter values estimated by bottom-up parameter extraction algorithms. It is shown that replacing PMU components with these autogenerated hybrid automata-based abstract behavioral models enables significant simulation speedup (> 20X on our industrial test cases) and helps in early detection of integration errors. The article also justifies the level of accuracy in our models with respect to the goal of verifying integrated PMUs. The approach presented in this work is implemented in the form of a tool suite called Chassis.

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“…Thus, in the past years several simplification techniques have been developed to reduce the complexity of the symbolic equation system within a given error bound. Initially designed for linear circuits, they have been adapted and extended to handle nonlinear analog circuits as well [1]. We will not go into the details of the simplification algorithms for nonlinear DAE systems.…”

Section: The Simplification Algorithmmentioning

confidence: 99%

Transient RankingMethods for the Simplification of Nonlinear DAE Systems in Analog Circuit Design

Wichmann

2003

Proc Appl Math and Mech

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Symbolic behavioral model generation of nonlinear analog circuits

Cited by 32 publications

References 30 publications

A behavioural modelling technique for visual microprocessor mixed‐signal VLSI chips

A behavioural modelling technique for visual microprocessor mixed‐signal VLSI chips

Chassis

Transient RankingMethods for the Simplification of Nonlinear DAE Systems in Analog Circuit Design

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