Titlebook: Analog IC Placement Generation via Neural Networks from Unlabeled Data; António Gusm?o,Nuno Horta,Ricardo Martins Book 2020 The Author(s),

燕麥

才能

CLEFT

Conclusions and Future Work,This chapter wraps up this book and present some future directions for further applications of ANNs towards the automation of the placement process of analog integrated circuit layout design.

hypotension

atopic

中世紀(jì)

ANN Models for Analog Placement Automation,ictions. Attention is placed into the development of the input features in order to expand the solution’s scope and increase generalization, and, the introduction of a new loss function that evaluates the prediction made through the fulfillment of the circuit’s topological constraints.

平靜生活

https://doi.org/10.1007/978-3-322-99411-0ration and the limitations that the current design flow faces. The standard procedures are presented. Furthermore, the concept of machine learning and the use of this branch of artificial intelligence as a step towards the production of electronic design automation tools for analog and mixed signal

步履蹣跚

adjacent

Hans-Jürgen Dotzler,Siegfried Schickictions. Attention is placed into the development of the input features in order to expand the solution’s scope and increase generalization, and, the introduction of a new loss function that evaluates the prediction made through the fulfillment of the circuit’s topological constraints.

委屈

https://doi.org/10.1007/978-3-030-50061-0Analog IC Placement; Artificial Neural Networks; Machine Learning; Electronic Design Automation; ANNs; An