Optimizing the Random Offset Voltage in Two Stage Amplifier Considering Noise-Power Trade-off Using HWPSO Algorithm

In this paper, the new Hybrid Whale Particle Swarm Optimization (HWPSO) algorithm is employed in minimizing the random offset voltage in a two stage Operational Amplifiers. Random offset voltage arises in due to transistor mismatch and imposes a restriction on the precision of specifications such as Gain, CMRR etc. obtained using the amplifier. This is more significant in case of low frequency applications such as in Neural or Biomedical. In order to minimize random offset an inherent tradeoff with the circuit area has to be met. Additionally, one of the prime requirements for these low frequency amplifiers is the need of low power as well as low noise. A specialized design approach is used as design constraint in this work to achieve a striking balance between these two design specifications i.e. Noise and Power while minimizing the random offset. Simulations are performed and comparative analysis illustrated that the HWPSO algorithm outperforms other state of art algorithms by giving a minimum random offset voltage of 1.638 mV with a circuit area of 3.51 × 10−9 m2. An optimal input noise of 28.24 nV/√Hz and power of 3.12 mW is obtained. Validation of HWPSO results have been done by performing simulations in Cadence Virtuoso, which are found to be in close agreement with the algorithmic results.

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