Constrained Optimization Applied to the Parameter Setting Problem for Analog Circuits

Abstract

We use constrained optimization to select operating parameters for two circuits: a simple 3-transistor square root circuit, and an analog VLSI artificial cochlea. This automated method uses computer controlled mea(cid:173) surement and test equipment to choose chip parameters which minimize the difference between the actual circuit's behavior and a specified goal behavior. Choosing the proper circuit parameters is important to com(cid:173) pensate for manufacturing deviations or adjust circuit performance within a certain range. As biologically-motivated analog VLSI circuits become increasingly complex, implying more parameters, setting these parameters by hand will become more cumbersome. Thus an automated parameter setting method can be of great value [Fleischer 90]. Automated parameter setting is an integral part of a goal-based engineering design methodology in which circuits are constructed with parameters enabling a wide range of behaviors, and are then "tuned" to the desired behaviors automatically.

Cite

Text

Kirk et al. "Constrained Optimization Applied to the Parameter Setting Problem for Analog Circuits." Neural Information Processing Systems, 1991.

Markdown

[Kirk et al. "Constrained Optimization Applied to the Parameter Setting Problem for Analog Circuits." Neural Information Processing Systems, 1991.](https://mlanthology.org/neurips/1991/kirk1991neurips-constrained/)

BibTeX

@inproceedings{kirk1991neurips-constrained,
  title     = {{Constrained Optimization Applied to the Parameter Setting Problem for Analog Circuits}},
  author    = {Kirk, David and Fleischer, Kurt and Watts, Lloyd and Barr, Alan},
  booktitle = {Neural Information Processing Systems},
  year      = {1991},
  pages     = {789-796},
  url       = {https://mlanthology.org/neurips/1991/kirk1991neurips-constrained/}
}