Abstract

Artificial hydrocarbon networks (AHNs) present several characteristics that are useful for learning, classifying, predicting, analyzing, filtering and controlling tasks, as described in previous chapters. Precisely, CH-molecules in their structures allow to capture and to cluster information about systems that can be exploited to solve engineering problems. In that sense, artificial hydrocarbon networks can be applied successfully in many real-world engineering applications. Thus, this chapter presents three different applications in which artificial hydrocarbon networks have been implemented, such as: design of adaptive filters for noisy audio signals, design of position controllers of direct current motors using the so-called AHN-fuzzy inference systems and design of a facial recognition system. Examples of program codes of these applications can be found in Appendix C.

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