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This paper focuses on the optimization of a fixed-topology MEMS accelerometer sensor using the MOEA/D evolutionary algorithm. Several methodologies have been implemented for the optimization of MEMS sensors. These techniques are either based on sweeping several design parameters to achieve a good performance or focused on the sensitivity analysis to determine the effects of each design parameter in...
This paper focuses on the implementation of different techniques for the integration of yield estimation in the synthesis loop of analog integrated circuits (ICs). MOEA/D (Multi-Objective Evolutionary Algorithm with Decomposition) is considered to be a very powerful multi-objective optimization algorithm. For the consideration of yield, several techniques are discussed and three different yield-aware...
This paper focuses on the implementation of different techniques for the integration of yield in the synthesis loop of analog ICs. Several algorithms have been developed for multi-objective optimization. Among these optimizers, MOEA/D (Multi-Objective Evolutionary Algorithm with Decomposition) is known as a powerful synthesizer. By using MOEA/D, some quality checks on practical designs have been realized...
It is known that the operating-point driven (OPD) analog sizing methods have clear advantages compared with the sizing methods of directly using transistor width and length as the decision variables. However, new analog sizing algorithms using OPD technique in modern technologies have seldom been reported in recent years. One of the main reasons is that with the scaling down of the technologies, the...
Recently, a multiobjective evolutionary algorithm based on decomposition (MOEA/D) and its extended version by using differential evolution (DE) as the main search engine (MOEA/D-DE) were proposed, which outperform several widely used multiobjective evolutionary algorithms. MOEA/D decomposes a multiobjective problem into a number of scalar optimization sub-problems with a neighborhood structure and...
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