Advances in Artificial Neural Networks comprises 17 expert-authored chapters based on high-quality global research. It provides the reader with varied insights into the many fascinating applications of neural networks across scientific disciplines. The first part of the book emphasizes architectures, and discusses topics such as an improved Kohonen feature map, the two-term back-propagation network, and MLP and ANFIS. In the second part, question of application are examined. Topics include applications in aquatic ecology, economic time series forecasting, and mineral potential mapping. In the third part, biomedical applications are in focus. Chapters discuss topics including pixel-based ANN for diagnosis, ANN in predictive medicine, estimation of the depth of anaesthesia, and ANN for gait classification and monitoring of post-stroke patients. The fourth part of the book brings industrial and control engineering applications to the fore. Subjects include a review of ANN in the textiles industry, ANN in meat production and technology, ANN application in induction motors, signal diagnostic systems and serial robot manipulators. This wide-ranging book will appeal to a variety of readers in scientific, medical, technical and industrial fields seeking enhanced understanding of how artificial neural networks may be applied in their work
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