Classification of analog synthesis tools based on their architecture selection mechanisms
Integration, the VLSI Journal
Review: Neuromolecularware and its application to pattern recognition
Expert Systems with Applications: An International Journal
Analog circuit optimization system based on hybrid evolutionary algorithms
Integration, the VLSI Journal
A memetic approach to the automatic design of high-performance analog integrated circuits
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Learning with a Quadruped Chopstick Robot
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
| Hi-index | 0.00 |
This paper presents an application of evolutionary programming to parameter optimization in the design of a voltage reference circuit. Designing circuits consists of two steps: topological design and parameter determination. After designing a topology suitable for the circuit, the designer selects an appropriate value for each circuit element from a circuit analysis and his experience. This step is difficult and time consuming because the designer must consider many factors simultaneously. As more precise circuits are required, parameter optimization becomes more complex. The voltage reference circuit, which requires a precise reference voltage independent of power fluctuation and temperature change, is such an example. In this paper, evolutionary programming is used as an effective method of finding good parameter values for the elements of the voltage reference circuit. Simulation results show that this method provides good performance and can be used as an effective method for circuit design