This collection presents cutting-edge research in neural networks from the 10th International Symposium on Neural Networks (ISNN 2013). The proceedings, divided into two volumes, feature 157 carefully selected papers that explore a wide array of topics within the field. These papers cover theoretical advancements in neural network models, learning algorithms, and stability analysis, as well as practical applications in areas such as computational neuroscience, cognitive science, robotics, bioinformatics, and data mining. The symposium aimed to foster discussion and disseminate new findings among researchers and practitioners in neural networks and related disciplines.

This volume represents a significant compilation of research presented at the ISNN 2013 conference, indicating a focus on established and emerging topics within neural networks. The breadth of subjects covered suggests a comprehensive overview of the field's state-of-the-art at the time of publication. The inclusion of both theoretical and applied research points to a text that would appeal to academics and professionals engaged in advanced study and development of neural network technologies.