학술논문

Non-regression approach for the behavioral model generator in mixed-signal system verification
Document Type
Conference
Source
2017 IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC) Very Large Scale Integration (VLSI-SoC), 2017 IFIP/IEEE International Conference on. :1-5 Oct, 2017
Subject
Components, Circuits, Devices and Systems
Computing and Processing
Integrated circuit modeling
Analytical models
Mathematical model
Timing
Calibration
Analog circuits
Generators
behavioral model
mixed-signal circuit
model generator
Language
ISSN
2324-8440
Abstract
Building the behavioral model for each analog circuit is an efficient approach for mixed-signal system verification. If an automatic model generator is available, it is useful for designers to reduce the extra efforts. Instead of modeling the relationship between circuit inputs and outputs directly, a divide and conquer approach is proposed in [8] to divide the circuit into several small building blocks and model the behavior of each block easily. Although the regression efforts have been greatly alleviated in this structure-based approach, the preparation of the training patterns is still a big issue. In this work, a different approach is proposed to build the behavioral model of each internal block in structure-based approach without regression. Therefore, no training patterns are required in the calibration process. As shown in the experimental results, the model accuracy is still kept in the proposed approach while the efficiency of behavioral model generator is greatly improved.