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首页> 外文期刊>International journal of electrical engineering and technology >Synthesis of On-Chip Square Spiral Inductors for RFIC's using Artificial Neural Network Toolbox and Particle Swarm Optimization
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Synthesis of On-Chip Square Spiral Inductors for RFIC's using Artificial Neural Network Toolbox and Particle Swarm Optimization

机译:基于人工神经网络工具箱和粒子群算法的RFIC片上方形螺旋电感器合成

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In this paper on-chip square spiral inductors are designed using ANN modeling techniques. Layout geometries form the input of the ANN model and electrical quantities forms the output. The dependency of inductor performances such as inductance (L), quality factor (Q) and self-resonance frequency (SRF) on geometric dimensions are described. Spirals of wide range of RF applications are studied. In our ANN based synthesis approach on-chip spiral inductor layout parameters such as spiral outer diameter(D), width of metal trace(W), number of turns in spiral(N), spacing between the adjutants metal traces(S) are taken as input and Inductance, Q-factor and Self resonance frequency are the output of our model. Further a PSO based searching algorithm is applied with ANN model for optimization of layout parameters for the electrical parameters. We present several synthesis results which show good accuracy with respect to full-wave electromagnetic (EM) simulations. Since the proposed procedure does not require a time consuming EM simulation in the synthesis loop, it substantially reduces the cycle time in RF-circuit design optimization.
机译:在本文中,使用ANN建模技术设计了片上方形螺旋电感器。布局几何构成ANN模型的输入,电量构成输出。描述了诸如电感(L),品质因数(Q)和自谐振频率(SRF)等电感器性能对几何尺寸的依赖性。研究了各种射频应用的螺旋。在我们基于ANN的综合方法中,采用了片上螺旋电感器布局参数,例如螺旋外径(D),金属走线宽度(W),螺旋线匝数(N),辅助金属走线之间的间距(S)作为输入和电感,Q因子和自谐振频率是我们模型的输出。此外,基于PSO的搜索算法与ANN模型一起用于优化电参数的布局参数。我们提出了几种综合结果,这些结果在全波电磁(EM)仿真方面显示出良好的准确性。由于拟议的程序不需要在合成环路中进行耗时的EM仿真,因此可以大大减少RF电路设计优化中的周期时间。

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