An exceptional effort has been extended in making a computer recognize both typed and handwritten characters automatically. Quite recent still today, the characters of English Language is been the main explore area for our researchers. Tamil under Asian languages has little or no attention is been given. The challenges posed by Indian languages are different from English. In addition, there has...

ARTICLE INFO ABSTRACT Keywords: Air pollution Meteorological variables Artificial neural networks Self-Organizing Maps (SOM) Clustering Salamanca is cataloged as one of the most polluted cities in Mexico. In order to observe the behavior and clarify the influence of wind parameters on the Sulphur Dioxide (S0 2) concentrations a Self-Organizing Maps (SOM) Neural Network have been implemented at ...

Healthy individuals show robust functional connectivity during rest, which is stronger in adults than in children. Connectivity occurs between the posterior and anterior portions of the default network, a group of structures active in the absence of a task, including the posterior cingulate cortex and the superior frontal gyrus. Previous studies found weaker posterior-anterior connectivity in t...

Humans have dramatically increased the deposition and availability of nutrients, such as nitrogen (N), worldwide. Soil organic matter (SOM) is a significant global reservoir of carbon (C); however, the effects of N enrichment on this large, heterogeneous C stock are unclear. Nitrogen has variable effects on the biological, chemical, and physical factors that determine SOM pool mean residence ti...

The model system between peanut yield and agronomy characteristics which is nonlinear, irreversible and dissipative. The objective in the study was the peanut cultivated in the different ecological regions in Shandong province, aimed to establish the new non-nonlinear model based on Self-Organizing Maps (SOM) to improve the cultivation information of peanut growth process. In the article, apply...

The work is related to the use of Self Organizing Map (SOM) which is a type of unsupervised Artificial Neural Network (ANN), as an aid to Maximal Ratio Combining (MRC) in order to improve bit error rate (BER) values of demodulated signals in wireless channels that have both Gaussian and multipath fading characteristics. Among the architectures and algorithms suggested for ANN, the SOM has the s...

Image segmentation has been and is likely to be an important component of the content-based image acquisition and retrieval systems. This paper describes a new method for segmentation of color images. The proposed method uses two phases segmentation processes. In the 1 phase, segmentation is performed with the help of cluster validity measures and Spatial Fuzzy C-Mean (sFCM). HSV model helps in...

This paper presents a technique in classifying the images into a number of classes or clusters desired by means of Self Organizing Map (SOM) Artificial Neural Network method. A number of 250 color images to be classified as previously done some processing, such as RGB to grayscale color conversion, color histogram, feature vector selection, and then classifying by the SOM Feature vector selecti...

Speech recognition has gradually improved over the years, phoneme recognition in particular. Phoneme recognition plays very important role in speech processing. Phoneme strings are basic representation for automatic language recognition and it is proved that language recognition results are highly correlated with phoneme recognition results. Nowadays, many recognizers are based on Artificial ne...

The image inpainting is a well-known task of visual editing. However, the efficiency strongly depends on sizes and textural neighborhood of “missing” area. Various methods of image inpainting exist, among which the Kohonen Self-Organizing Map (SOM) network as a mean of unsupervised learning is widely used. The weaknesses of the Kohonen SOM network such as the necessity for tuning of algorithm p...