Performance parameters optimization of CMOS analog signal processing circuits based on smart algorithms

Abstract

Designing ideal analogue circuits has become difficult due to extremely large-scale integration. The complementary metal oxide semiconductor (CMOS) analog integrated circuits (IC) could use an evolutionary method to figure out the size of each device. The CMOS operational transconductance amplifier (CMOS OTA) and the CMOS current conveyor second generation (CMOS CCII) are designed using advanced nanometer transistor technology (180 nm). Both CMOS OTA and CMOS CCII have high performance, such as a wide frequency, voltage gain, slew rate, and phase margin, to include very wide applications in signal processing, such as active filters and oscillators. The optimization approach is an iterative procedure that uses an optimization algorithm to change design variables until the optimal solution is identified. In this study, different sorts of algorithms the genetic algorithm (GA), particle swarm optimization (PSO), and cuckoo search (CS) are employed to boost and enhance the performance parameters. While decreasing the time required to develop a conventional operation amplifier's settling time. Some studies decrease the value of the power utilized at various frequencies. Others operate at extremely high frequencies, but their power consumption is greater than that of those operating at lower frequencies.