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Journal of Learning & Nonlinear Models

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The Learning & Nonlinear Models (L&NLM) journal is a pioneering initiative of the Brazilian Society of Neural Networks and Computational Intelligence (SBRN/SBIC), whose goal is to foster the academic and professional scientific production in the fields of Computational Intelligence (CI) and Nonlinear Systems (NLS). The L&NLM journal invites authors to submit theory- or application-oriented articles from the most diverse areas within CI/NLS, such as artificial neural networks, fuzzy systems, evolutionary computation, swarm intelligence, machine learning, data mining, time series prediction, chaotic system modeling and control, system identification, robotics, biomedicine and bioengineering, fault detection and identification, biometric systems, signal and image processing, nonlinear control systems, telecommunications, among others. Survey papers on the state of the art of any of the aforementioned topics are also welcome.

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