Abstract
Over the last years, there has been a great increase in interest in studying biological systems to develop new approaches for solving difficult engineering problems. Artificial neural networks, evolutionary computation, ant colony system and artificial immune system are some of these approaches. In the literature, there are several models proposed for neural network and evolutionary computation to many different problems from different areas. However, the immune system has not attracted the same kind of interest from researchers as neural network or evolutionary computation. An artificial immune system implements a learning technique inspired by human immune system. In this work, a novel method based on artificial immune algorithm is described to component value selection for analog active filters.
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Kalinli, A. (2004). Optimal Circuit Design Using Immune Algorithm. In: Nicosia, G., Cutello, V., Bentley, P.J., Timmis, J. (eds) Artificial Immune Systems. ICARIS 2004. Lecture Notes in Computer Science, vol 3239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30220-9_4
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DOI: https://doi.org/10.1007/978-3-540-30220-9_4
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