... networks”, IEEE Transactions on 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20 ... Algorithms and Applications, McGraw-Hill, 1996. 6. Cichocki A., Unbehauen R ... Divide and conquer algorithms for constructing neural network architectures ...

Organized by application areas, rather than by specific network architectures or learning algorithms, Building Neural Networks shows why certain networks are more suitable than others for solving specific kinds of problems.

Explains current co-design and co-optimization methodologies for building hardware neural networks and algorithms for machine learning applications This book focuses on how to build energy-efficient hardware for neural networks with ...

Proceedings of the International Conference on Artificial Neural Networks Amsterdam, The Netherlands 13–16 September 1993 Stan Gielen, Bert Kappen. Prove of Convergence of Extended Divide & Conquer ... algorithms were proposed for dynamically ...

In my opinion, this can be attributed to poor network design owing to misconceptions regarding how neural networks work. This book discusses every aspect of the artificial neural network in very interactive, practical and simple way.

... neural networks and genetic algorithms . The first such event was held in ... construct the most effective network architecture for the problem in hand ... divide and conquer approach is adopted and each module is trained to solve a ...

The book concludes by examining various neural network applications, such as neuron-fuzzy control systems and image compression. This final part of the book also provides a case study involving oil spill detection.

... method for generation of a neural network architecture: a continuous 3D algorithm. IEEE Trans. Neural Networks 3:280–291, 1992. [100 T. Sanger. A tree-structured adaptive network for function approximation. Designing. Neural. Network.

This book presents a collection of invited works that consider constructive methods for neural networks, taken primarily from papers presented at a special th session held during the 18 International Conference on Artificial Neural Networks ...