The objective of this paper is to introduce an efficient algorithm, namely, the mathematically improved learning-self organizing map (MIL-SOM) algorithm, which speeds up the self-organizing map (SOM) training process. In the proposed MIL-SOM algorithm, the weights of Kohonen's SOM are based on the proportional-integral-derivative (PID) controller. Thus, in a typical SOM learning setting, this i...

A HARDWARE IMPLEMENTATION OF THE SOM FOR A NETWORK INTRUSION DETECTION SYSTEM Brent W. Roeder, B.S. Virginia Tech, 2005 Thesis Director: Dr. Kris Gaj This thesis describes the research and development of a hardware implementation of the self organizing map (SOM) for a network intrusion detection system. As part of the thesis research, Kohonen’s SOM algorithm was examined and different hardware ...

The Self Organizing Maps (SOM) is regarded as an excellent computational tool that can be used in data mining and data exploration processes. The SOM usually create a set of prototype vectors representing the data set and carries out a topology preserving projection from high-dimensional input space onto a low-dimensional grid such as two-dimensional (2D) regular grid or 2D map. The 2D-SOM tech...

Service-Oriented Manufacturing (SOM) strategy is a new manufacturing mode by integrating servitization with the traditional manufacturing industry. The advantages and importance of the SOM strategy are gradually recognized by more and more enterprises. However, the enterprises’ specific cost structures and cost configurations for providing customized services have influences on the decisions ab...

The self-organizing map (SOM) model is a well-known neural network model with wide spread of applications. The main characteristics of SOM are two-fold, namely dimension reduction and topology preservation. Using SOM, a high-dimensional data space will be mapped to some low-dimensional space. Meanwhile, the topological relations among data will be preserved. With such characteristics, the SOM w...

In the real world, it is not always true that the nextdoor house is close to my house, in other words, “neighbors” are not always “true neighbors”. In this study, we propose a new Self-Organizing Map (SOM) algorithm, SOM with False Neighbor degree between neurons (called FN-SOM). The behavior of FN-SOM is investigated with learning for various input data. We confirm that FN-SOM can obtain the m...

Nyberg F. Structural plasticity of the brain to psychostimulant use. Neuropharmacology. 2014; 87:115-124. Beroendeframkallande droger som de centrakstimulerande amfetamin, kokain, ecstasy, metyfenidater och även nikotin bidrar till förändringar i olika beteenden men också i hjärnans kemi och stuktur. De har vistas orsaka långvarig påverkan på nervcellernas dendriter och strukturer I regioner so...

Ten-month-old infants' sensitivity to first-order motion (FOM) defined by luminance and second-order motion (SOM) defined by flickering was measured in an eye-tracking paradigm. We used a small single disc or gratings moving horizontally. Although infants could track the SOM of a small disc, they failed to exhibit smooth pursuit eye movements. They also failed to track SOM gratings with smooth ...

Two well-known variants of the self-organizing map (SOM) that are based on order statistics are the marginal median SOM and the vector median SOM. In the past, their efficiency was demonstrated for color image quantization. In this paper, we employ the well-known IRIS data set and we assess their performance with respect to the accuracy, the average over all neurons mean squared error between t...