TurSOM: A Turing inspired Self-Organizing Map

TurSOM, short for Turing self-organizing map, introduces new concepts, responsibilities and mechanisms to the traditional SOM algorithm. It draws its inspiration from Turing unorganized machines, competitive learning techniques, and SOM algorithms. Turing´s unorganized machines (TUM) were one of the first computational concepts of modeling the cortex. Turing also described these machines as having self-organizing behaviors. The primary difference between Turing´s self-organization description, and more traditional models we are familiar with (Grossberg, Kohonen), are that connections, rather than neurons, self-organize. TurSOM adheres to unsupervised, competitive learning techniques, wherein all neurons, and all connections between them are self-organizing and competing. As such, it presents a novel self-organizing neural network algorithm that eliminates the need for post-processing methods for cluster identification.