Self-organization constitutes an important paradigm in machine learning with successful applications e.g. in dataand web-mining. Most approaches, however, have been proposed for processing data contained in a fixed and finite dimensional vector space. In this article, we will focus on extensions to more general data structures like sequences and tree structures. Various modifications of the sta...

Recently, security of the computer systems becomes an important problem. Almost all computers use the password mechanism for the user authentication. But password mechanism has many issues. In this paper, we propose a kind of biometrics authentication method using the combinations of key stroke timings and pen calligraphy. For this method, selection of the phrase is important. We analyzed the k...

Visual aura is a common migraine symptom. Prediction of their spatio-temporal evolution can help to understand the underlying etiology. Self-organization is used on the curved surface of the visual cortex to reproduce human retinotopy. The neural layer of the SOM algorithm is created by a novel approach to implement centroidal Voronoi tesselations on meshes. Realistic retinotopic maps are obtai...

The paper starts with the need for classification. Then the reasons why neural networks are suitable for document classification are explained. The paper continues with the details of the most commonly used topologically organized network model proposed by Kohonen (1982), referred to as the self-organizing map (SOM). The general idea proposed is to display the contents of a document library by ...

In some applications and in order to address real world situations better, data may be more complex than simple vectors. In some examples, they can be known through their pairwise dissimilarities only. Several variants of the Self Organizing Map algorithm were introduced to generalize the original algorithm to this framework. Whereas median SOM is based on a rough representation of the prototyp...

The Wilcoxon signed-rank test is exploited for document organization and retrieval in this paper. A novel modeling method for documents and a distance metric between documents are proposed. Both document modeling and document comparisons are based on signed-ranks and are applied to the frequency of occurrence of the document bigrams. A metric using the Wilcoxon signed-rank test exploits these s...

This paper intends to introduce an implementation of a novel Self-Organization Map (SOM) in Host-based Stepping Stone Detection (SSD). Previous works have introduced Artificial Intelligence (AI) approaches such as Artificial Neural Network (ANN), however we found that the approaches are complex due to the requirement of variable to be known and tested to detect a stepping stone. SOM provides un...

hot-wire spirometer uses a constant temperature anemometer (cta) for its operation. the working principle of cta, used for the measurement of fluid velocity and flow turbulence, is based on convective heat transfer from a hot-wire sensor to a fluid being measured. the calibration curve of a cta is nonlinear and cannot be easily extrapolated beyond its calibration range. therefore, a method for ...

We propose a new method called C-SOM for function approximation. C-SOM extends the standard Self-Organizing Map (SOM) with a combination of Local Linear Mapping (LLM) and cubic spline based interpolation techniques to improve standard SOMs' generalization capabilities. CSOM uses the gradient information provided by the LLM technique to compute a cubic spline interpolation in the input space bet...

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...