ABSTRACT A new efficient design approach for sizing a high-performance analog amplifier circuit namely the recycling folded cascode (RFC) amplifier is presented. An RFC amplifier is an enhanced version of the conventional folded cascode amplifier and achieves better slew rate, gain, bandwidth, offset, etc. for same area and power budget. Low-frequency amplifiers such as biomedical or neural have a demanding requirement of low area, low power, and low noise apart from meeting other optimal design specifications which have inherent trade-off among themselves. As a result, manual sizing becomes a computationally inefficient approach. Thus, swarm-based optimization techniques have been employed to efficiently determine the optimal sizing for the RFC amplifier such that the area is minimized while meeting all the optimal design specifications considering the constraints. A new hybrid whale particle swarm optimization (HWPSO) algorithm is employed which takes advantage of the good qualities of both the whale algorithm and the PSO algorithm to optimize the area with less computational complexity. Simulations and statistical analysis have been performed and comparisons with other state of art algorithms reveals that HWPSO-based approach achieves a minimum circuit area of 21 µm2 with a mean Friedman’s statistical rank of 2.05 while meeting optimal design specifications for low-frequency systems. Finally, validation with circuit design tool Cadence Virtuoso is done and pre- as well as postlayout analysis have been performed which further illustrated a close agreement with algorithmic results.

中文翻译：

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使用新的基于混合群智能技术的低频应用循环折叠级联放大器的最佳尺寸

摘要 提出了一种新的有效设计方法，用于确定高性能模拟放大器电路的尺寸，即循环折叠共源共栅 (RFC) 放大器。RFC 放大器是传统折叠共源共栅放大器的增强版本，可在相同面积和功率预算下实现更好的压摆率、增益、带宽、偏移等。生物医学或神经等低频放大器除了满足其他具有内在折衷的优化设计规范外，还对小面积、低功率和低噪声提出了苛刻的要求。因此，手动调整大小成为一种计算效率低下的方法。因此，已经采用基于群的优化技术来有效地确定 RFC 放大器的最佳尺寸，以便在考虑约束的情况下满足所有最佳设计规范的同时最小化面积。采用新的混合鲸鱼粒子群优化（HWPSO）算法，利用鲸鱼算法和PSO算法的优点，以较少的计算复杂度优化区域。已经进行了模拟和统计分析，并与其他最先进的算法进行了比较，结果表明，基于 HWPSO 的方法实现了 21 µm2 的最小电路面积，平均弗里德曼统计等级为 2.05，同时满足低频系统的最佳设计规范。最后，