The document discusses recent trends in using artificial neural networks (ANNs) for analog circuit design. It provides an introduction to analog design flows and challenges. ANNs can help automate analog circuit sizing and placement tasks. The document reviews literature on using ANNs for tasks like sizing circuits for different technologies and optimizing parameters. In conclusion, ANNs show promise for reducing analog design time and efforts by training on previous simulation data to optimize circuits.

1. A Seminar on
Recent Trends in Analog Circuit Design using ANN
Submitted By:
MITESH KALAL
(P19VL003)
Supervisor:
DEEPAK JOSHI
Assistant Professor, ECED
DEPARTMENT OF ELECTRONICS ENGINEERING
SARDAR V
ALLABHBHAI NA
TIONAL INSTITUTE OF TECHNOLOGY, SURAT
NOVEMBER 2020

2. Outline
December 6, 2021 Recent Trends in Analog Circuit Design Using ANN 2
Introduction
Analog Design Flow
ANN and Analog Circuit Design
Overview of ANN
Difficulties in Analog Circuit Design
Literature Survey
Summary

3. • Complexity of ICs is increasing day by
day.
• ICs or SoCs are implemented using
both Digital and Analog circuitry.
• Figure 1 represents the contrast
between the design efforts of analog
and digital blocks on SoCs or ICs [1].
• Designing of Analog part takes longer
time than Digital [2].
Introduction
December 6, 2021 Recent Trends in Analog Circuit Design Using ANN 3
Figure 1: Contrast between analog and digital blocks’ design effort
[1]. N. Lourenço, R. Martins, N. Horta,” Automatic Analog IC Sizing and Optimization
Constrained with PVT Corners and Layout Effects,” (Springer, 2017)
[2] R. Martins, N. Lourenço, N. Horta, “Analog Integrated Circuit Design Automation—Placement, Routing and Parasitic Extraction Techniques,” (Springer, Berlin, 2017)

4. Analog Design Flow
December 6, 2021 Recent Trends in Analog Circuit Design Using ANN 4
Figure 2: Design tasks of analog design flow
[1]. N. Lourenço, R. Martins, N. Horta,” Automatic Analog IC Sizing and Optimization
Constrained with PVT Corners and Layout Effects,” (Springer, 2017)

5. Overview of ANN
December 6, 2021 Recent Trends in Analog Circuit Design Using ANN 5
• ANN is a collection of connected neurons(nodes) shown in
Figure 4.
• A neuron sums its weighted inputs, passes that results through
a function called activation function and outputs that value.
• The process carried out by neuron in an ANN is shown in
Figure 5.
Figure 4: Representation of an artificial neuron
[3] K. Hornik, M. Stinchcombe, H. White, “Multilayer
feedforward networks are universalapproximators,” Neural
Netw. 2(5), 359–366 (1989)
Figure 5: Process carried by neuron in a Neural Network
[4] The Complete Guide to Artificial Neural Networks: Concepts and Models. Retrieved from: https://missinglink.ai/guides/neural-network-concepts/complete-guide-artificial-
neural-networks/ (November 2020)

6. Overview of ANN…
December 6, 2021 Recent Trends in Analog Circuit Design Using ANN 6
• Figure 6 shows the ANN with 2 hidden layers with all the training process.
Figure 6: ANN with 2 hidden layers
[P.C. : https://www.slideshare.net/ashokktiwari/ann-load-forecasting]

7. Activation Function and their Derivatives
December 6, 2021 Recent Trends in Analog Circuit Design Using ANN 7
• Activation Function determines
the output of the neural network.
• It is attached with each neuron to
decide whether the node should
be activated or not depending on
the input parameters.
• Derivatives of Activation
Functions are used for back
propagation to update the weights
of the neuron.
• Figure 7 shows the different
activation functions. Figure 7: Activation Functions
[https://engmrk.com/activation-function-for-dnn/]

8. • ML is the process in which a computer improves its capabilities through
the analysis of past experiences.
• Recent developments in ML opens a new research in EDA tools for
analog IC design.
• ANNs are capable of solving analog IC sizing as a direct map from
specifications to the device sizes [5].
• Using ANNs automation of two design tasks of an analog IC can be done:
1) Circuit Sizing
2) Placement
ANN and Analog Circuit Design
December 6, 2021 Recent Trends in Analog Circuit Design Using ANN 8

9. ANN for Circuit Sizing
December 6, 2021 Recent Trends in Analog Circuit Design Using ANN 9
Figure 8: Circuit Sizing using ANN
[5] João P. S. Rosa, Daniel J. D. Guerra, Nuno C. G. Horta, Ricardo M. F. Martins and Nuno C. C. Lourenço,” Using Artificial Neural Networks for Analog Integrated Circuit Design Automation,” (Springer, 2019)

10. ANN for Placement
December 6, 2021 Recent Trends in Analog Circuit Design Using ANN 10
Figure 8: ANN for Placement
[5] João P. S. Rosa, Daniel J. D. Guerra, Nuno C. G. Horta, Ricardo M. F. Martins and Nuno C. C. Lourenço,” Using Artificial Neural Networks for Analog Integrated Circuit Design Automation,” (Springer, 2019)

11. • Lack of systematic design flows supported by EDA tools.
• Integration of analog circuits using technologies optimized for digital
circuits.
• Difficulty in reusing analog blocks because they are sensitive to
surrounding circuitry and environmental and process variations.
• As the technology is scaling down square law equation is not followed
and thus optimization is difficult.
Difficulties in Analog Circuit Design
December 6, 2021 Recent Trends in Analog Circuit Design Using ANN 11

12. Sr. no. Paper Paper Description
[1] G. İslamoğlu, T. O. Çakici, E. Afacan and G.
Dündar, "Artificial Neural Network Assisted Analog
IC Sizing Tool," 2019 16th International Conference
on Synthesis, Modeling, Analysis and Simulation
Methods and Applications to Circuit Design
(SMACD), Lausanne, Switzerland, 2019, pp. 9-12,
doi: 10.1109/SMACD.2019.8795293.
• This paper proposes utilization of neural networks to estimate circuit performance
and hence, reduce the execution time.
• Two circuits, Single stage current mirror based differential amplifier and folded
cascode OTA are taken for case study.
[2] A. Jafari, S. Sadri and M. Zekri, "Design
optimization of analog integrated circuits by using
artificial neural networks," 2010 International
Conference of Soft Computing and Pattern
Recognition, Paris, 2010, pp. 385-388, doi:
10.1109/SOCPAR.2010.5686736.
• In this paper neural network is used in order to find a set of circuit parameters
such that the design objectives are optimized while satisfying performance
constraints for different Op-Amp topologies.
[3] N. Kahraman and T. Yildirim, "Technology
independent circuit sizing for fundamental analog
circuits using artificial neural networks," 2008
Ph.D. Research in Microelectronics and
Electronics, Istanbul, 2008, pp. 1-4, doi:
10.1109/RME.2008.4595710.
• In this paper ANN is trained with data of different technologies to give the
transistor sizes of circuit for an unknown technology that has not been trained
before.
• Trained technologies: 1.5um, 0.5um, 0.35um, 0.25um. Test Technology: 0.18um
[4] Qi-Jun Zhang, K. C. Gupta and V. K.
Devabhaktuni, "Artificial neural networks for RF
and microwave design - from theory to practice,"
in IEEE Transactions on Microwave Theory and
Techniques, vol. 51, no. 4, pp. 1339-1350, April
2003, doi: 10.1109/TMTT.2003.809179.
• In this paper ANN is used to design and optimize RF and microwave circuits.
Neural networks are trained to learn the behavior of passive/active
components/circuits.
Literature Survey
December 6, 2021 Recent Trends in Analog Circuit Design Using ANN 12

13. Literature Survey
December 6, 2021 Recent Trends in Analog Circuit Design Using ANN 13
Ref. no. Author Paper Description
[5] M. Seok, M. Yang, Z. Jiang, A. A. Lazar and J. Seo,
"Cases for Analog Mixed Signal Computing
Integrated Circuits for Deep Neural Networks,"
2019 International Symposium on VLSI Design,
Automation and Test (VLSI-DAT), Hsinchu,
Taiwan, 2019, pp. 1-2, doi: 10.1109/VLSI-
DAT.2019.8742044.
• In this paper, the emerging analog and mixed-signal circuit techniques to improve
energy efficiency using ANN are discussed.
• This paper has reviewed on two such techniques, one on the speech recognition
processor in hybrid analog and digital circuits and the other on the embedded
SRAM circuits that support analog-mixed-signal in-memory (in-bitcell)
computing for convolutional and deep neural networks.
[6] A. Viveros-Wacher and J. E. Rayas-Sánchez,
"Analog Fault Identification in RF Circuits using
Artificial Neural Networks and Constrained
Parameter Extraction," 2018 IEEE MTT-S
International Conference on Numerical
Electromagnetic and Multiphysics Modeling and
Optimization (NEMO), Reykjavik, 2018, pp. 1-3,
doi: 10.1109/NEMO.2018.8503117.
• Authors explain about fault diagnosis problem in analog circuits and an ANN
based modeling approach to efficiently emulate the injection of analog faults in
the circuits.
[7] Guerra, A. Canelas, R. Póvoa, N. Horta, N.
Lourenço and R. Martins, "Artificial Neural
Networks as an Alternative for Automatic Analog
IC Placement," 2019 16th International Conference
on Synthesis, Modeling, Analysis and Simulation
Methods and Applications to Circuit Design
(SMACD), Lausanne, Switzerland, 2019, pp. 1-4,
doi: 10.1109/SMACD.2019.8795267.
• Authors explain, use of ANNs for automation of the placement task of analog IC
layout design.
• ANNs were trained with the data of different layout structures of analog circuit
and gives different placement alternatives as output.

14. • Analog IC designing is not as fast as digital design.
• Many sources and technology are available for designing of digital circuits.
• For SoCs, designing of analog circuits is equally important as digital circuits.
• Designing of analog circuits takes longer time and less immune to noise compared to digital.
• As the circuit complexity increases the designing time and efforts increases.
• To reduce the designing time with less human efforts ANN is one of the prominent field for optimization in
analog IC designing.
• The network is trained with the data of previous simulations and used to optimize the circuit parameters and
size.
• ANN can also be trained for placement task in IC layout design.
• ANN has great scope in field of analog IC design automation for circuit sizing and placement.
Summary
December 6, 2021 Recent Trends in Analog Circuit Design Using ANN 14

15. [1] N. Lourenço, R. Martins, N. Horta,” Automatic Analog IC Sizing and Optimization Constrained with PVT Corners and Layout Effects,” (Springer, 2017)
[2] R. Martins, N. Lourenço, N. Horta, “Analog Integrated Circuit Design Automation—Placement, Routing and Parasitic Extraction Techniques,” (Springer, Berlin, 2017)
[3] K. Hornik, M. Stinchcombe, H. White, “Multilayer feedforward networks are universalapproximators,” Neural Netw. 2(5), 359–366 (1989)
[4] The Complete Guide to Artificial Neural Networks: Concepts and Models. Retrieved from: https://missinglink.ai/guides/neural-network-concepts/complete-guide-artificial-neural-networks/
(November 2020)
[5] João P. S. Rosa, Daniel J. D. Guerra, Nuno C. G. Horta, Ricardo M. F. Martins and Nuno C. C. Lourenço,” Using Artificial Neural Networks for Analog Integrated Circuit Design Automation,”
(Springer, 2019)
[6] G. İslamoğlu, T. O. Çakici, E. Afacan and G. Dündar, "Artificial Neural Network Assisted Analog IC Sizing Tool," 2019 16th International Conference on Synthesis, Modeling, Analysis and
Simulation Methods and Applications to Circuit Design (SMACD), Lausanne, Switzerland, 2019, pp. 9-12, doi: 10.1109/SMACD.2019.8795293.
[7] A. Jafari, S. Sadri and M. Zekri, "Design optimization of analog integrated circuits by using artificial neural networks," 2010 International Conference of Soft Computing and Pattern
Recognition, Paris, 2010, pp. 385-388, doi: 10.1109/SOCPAR.2010.5686736.
[8] N. Kahraman and T. Yildirim, "Technology independent circuit sizing for fundamental analog circuits using artificial neural networks," 2008 Ph.D. Research in Microelectronics and
Electronics, Istanbul, 2008, pp. 1-4, doi: 10.1109/RME.2008.4595710.
[9] Qi-Jun Zhang, K. C. Gupta and V. K. Devabhaktuni, "Artificial neural networks for RF and microwave design - from theory to practice," in IEEE Transactions on Microwave Theory and
Techniques, vol. 51, no. 4, pp. 1339-1350, April 2003, doi: 10.1109/TMTT.2003.809179.
[10] M. Seok, M. Yang, Z. Jiang, A. A. Lazar and J. Seo, "Cases for Analog Mixed Signal Computing Integrated Circuits for Deep Neural Networks," 2019 International Symposium on VLSI
Design, Automation and Test (VLSI-DAT), Hsinchu, Taiwan, 2019, pp. 1-2, doi: 10.1109/VLSI-DAT.2019.8742044.
[11] A. Viveros-Wacher and J. E. Rayas-Sánchez, "Analog Fault Identification in RF Circuits using Artificial Neural Networks and Constrained Parameter Extraction," 2018 IEEE MTT-S
International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization (NEMO), Reykjavik, 2018, pp. 1-3, doi: 10.1109/NEMO.2018.8503117.
[12] Guerra, A. Canelas, R. Póvoa, N. Horta, N. Lourenço and R. Martins, "Artificial Neural Networks as an Alternative for Automatic Analog IC Placement," 2019 16th International Conference
on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD), Lausanne, Switzerland, 2019, pp. 1-4, doi: 10.1109/SMACD.2019.8795267.
References
December 6, 2021 Recent Trends in Analog Circuit Design Using ANN 15