The Backtracking Search for the Optimal Design of Low-Noise Amplifiers

The backtracking search algorithm (BSA) was recently developed. It is an evolutionary algorithm for real-valued optimization problems. The main feature of BSA vis-a-vis other known evolutionary algorithms is that it has a single control parameter. It has also been shown that it has a better convergence behavior. In this chapter, the authors deal with the application of BSA to the optimal design of RF circuits, namely low-noise amplifiers. BSA performance, viz. robustness and speed, are checked against the widely used particle swarm optimization technique, and other published approaches. ADS simulation results are given to show the viability of the obtained results.

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