The Kohonen self-organizing map (SOM) is an important tool to find a mapping from high-dimensional space to low dimensional space. The time a SOM requires increases with the number of neurons. A parallel implementatio...The Kohonen self-organizing map (SOM) is an important tool to find a mapping from high-dimensional space to low dimensional space. The time a SOM requires increases with the number of neurons. A parallel implementation of the algorithm can make it faster. This paper investigates the most recent parallel algorithms on SOMs. Using Java network programming utilities, improved parallel and distributed system are set up to simulate these algorithms. From the simulations, we conclude that those algorithms form good feature maps.展开更多
文摘The Kohonen self-organizing map (SOM) is an important tool to find a mapping from high-dimensional space to low dimensional space. The time a SOM requires increases with the number of neurons. A parallel implementation of the algorithm can make it faster. This paper investigates the most recent parallel algorithms on SOMs. Using Java network programming utilities, improved parallel and distributed system are set up to simulate these algorithms. From the simulations, we conclude that those algorithms form good feature maps.
