Source: http://ceperic.info/?cat=5
Timestamp: 2019-04-25 18:06:17+00:00

Document:
Circuit simulations at the system level are one of the most complex tasks that engineers encounter in the field of electronics and microelectronics due to two main reasons: the low speed and limited accuracy of circuit simulations. The black-box approach to behavioural modelling of electronic circuits, although very challenging, is particularly interesting for fast and relatively accurate simulations of analogue and mixed-signal integrated circuits. Today’s most prevalent approach is manual generation of the black-box models, which is heuristic, inconvenient, computationally expensive and error-prone. Automated model-building has many potential benefits. It is however very difficult to develop a fully automated model generation procedure because the model has to cover a wide range of circuits and devices. In this research several methods are proposed that can be regarded as essential blocks needed for the automated generation of black-box models. The new methods of functional approximation (ALSVR, TASVR and MK-ALSVR) suitable for the black-box modelling of electronic circuits are proposed. The new algorithm FTSR is proposed for model inputs selection and ranking as well as training data points selection and ranking, designed specifically for black-box modelling of electronic circuits. Also, a new method for checking and improving the stability of black-box electronic circuit models (CISB) is presented. It enables models built from the proposed behavioural modelling procedures to be effectively implemented in common circuit simulation tools. A new machine learning approach to modelling of conducted electromagnetic emissions and conducted electromagnetic immunity is proposed. Finally, the framework for behavioural modelling of electronic circuits based on the methods proposed is proposed.
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This entry was posted in Black-box modelling, Electronic circuit modelling on August 26, 2014 by vceperic@gmail.com.

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