By Michael Eick, Helmut Graeb (auth.), Mourad Fakhfakh, Esteban Tlelo-Cuautle, Rafael Castro-Lopez (eds.)
Despite the truth that within the electronic area, designers can take complete merits of IPs and layout automation instruments to synthesize and layout very complicated platforms, the analog designers’ job remains to be regarded as a ‘handcraft’, bulky and extremely time eating strategy. hence, large efforts are being deployed to improve new layout methodologies within the analog/RF and mixed-signal domain names.
This publication collects sixteen state of the art contributions dedicated to the subject of systematic layout of analog, RF and combined sign circuits. Divided within the components Methodologies and methods contemporary theories, synthesis suggestions and layout methodologies, in addition to new sizing methods within the box of strong analog and combined sign layout automation are provided for researchers and R/D engineers.
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Additional info for Analog/RF and Mixed-Signal Circuit Systematic Design
In standard EAs, the solution quality of the population is improving in the evolution process; so beneficial information to generate promising candidates keeps increasing in the consecutive populations. After some iterations, a high percentage of the information in the current population is beneficial to generate a candidate with good quality. In contrast, for surrogate model-assisted optimization, besides the initial samples, only one or few good new individuals are evaluated and added to the population in each iteration to increase the efficiency.
The promising solutions are selected meanwhile and guide further candidate solution generation. The advantages on efficiency and reliability of on-line surrogate model-based optimization compared with off-line surrogate model-based optimization  are described and compared in . On the other hand, the challenge of on-line surrogate-model-based optimization is that the quality of the surrogate model is not always good, as it is improving gradually throughout the optimization process. If the training data is little in some area of the design space, especially in the beginning stage, not enough information can be provided to the learning machine, so the surrogate model might not be 2 Efficient Synthesis Methods for High-Frequency Integrated Passive Components 35 good enough.
An Efficient HighFrequency Linear RF Amplifier Synthesis Method Based on Evolutionary Computation and Machine Learning Techniques. : A synthesis tool for CMOS RF low-noise amplifier. : An efficient, fully parasitic-aware power amplifier design automation tool. : Layout-aware RF circuit synthesis driven by worst case parasitic corners. In: Proc. of ICCD, pp. : A synthesis flow toward fast parasitic closure for radio-frequency integrated circuits. In: Proc. of DAC, pp. : CYCLONE: automated design and layout of RF LC-Oscillators.