Since their re-popularisation in the mid-1980s, artificial neural networks have seen an explosion of research across a diverse spectrum of areas. While an immense amount of research has been undertaken in artificial neural networks themselves--in terms of training, topologies, types, etc.--a similar amount of work has examined their application to a whole host of real-world problems. Such problems are usually difficult to define and hard to solve using conventional techniques. Examples include computer vision, speech recognition, financial applications, medicine, meteorology, robotics,...
Since their re-popularisation in the mid-1980s, artificial neural networks have seen an explosion of research across a diverse spectrum of areas. W...
