• Title Recurrent Neural Networks and Soft Computing
• Author(s) Mahmoud ElHefnawi and Mohamed Mysara
• Publisher: IN-TECH (March 30, 2012); eBook (Creative Commons Licensed)
• License(s): Attribution 3.0 Unported (CC BY 3.0)
• Hardcover 304 pages
• Language: English
• ISBN-10: N/A
• ISBN-13: 978-953-51-0409-4
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Book Description

New applications in recurrent neural networks are covered by this book, which will be required reading in the field. Methodological tools covered include ranking indices for fuzzy numbers, a neuro-fuzzy digital filter and mapping graphs of parallel programmes. The scope of the techniques profiled in real-world applications is evident from chapters on the recognition of severe weather patterns, adult and foetal ECGs in healthcare and the prediction of temperature time-series signals.

Additional topics in this vein are the application of AI techniques to electromagnetic interference problems, bioprocess identification and I-term control and the use of BRNN-SVM to improve protein-domain prediction accuracy. Recurrent neural networks can also be used in virtual reality and nonlinear dynamical systems, as shown by two chapters.

• Dr Mahmoud ElHefnawi is the the Biomedical informatics and Chemoinformatics group leader at the Centre of Excellence for Advanced Sciences(CEAS) and Informatics and Systems Department, National Research Centre NRC).

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• Neural Networks and Deep Learning
• Machine Learning
• Artificial Intelligence

• Recurrent Neural Networks and Soft Computing (Mahmoud ElHefnawi, et al)
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