نتایج جستجو برای: som

تعداد نتایج: 8723  

2016
Ryotaro Kamimura

In this paper, we introduce a new type of information-theoretic method called “information-theoretic active SOM”, based on the self-organizing maps (SOM) for training multi-layered neural networks. The SOM is one of the most important techniques in unsupervised learning. However, SOM knowledge is sometimes ambiguous and cannot be easily interpreted. Thus, we introduce the information-theoretic ...

Journal: :The Journal of neuroscience : the official journal of the Society for Neuroscience 2010
Wen-pei Ma Bao-hua Liu Ya-tang Li Z Josh Huang Li I Zhang Huizhong W Tao

Somatostatin-expressing inhibitory (SOM) neurons in the sensory cortex consist mostly of Martinotti cells, which project ascending axons to layer 1. Due to their sparse distribution, the representational properties of these neurons remain largely unknown. By two-photon imaging guided cell-attached recordings, we characterized visual response and receptive field (RF) properties of SOM neurons an...

Journal: :Journal of molecular graphics & modelling 2014
Yayun Sheng Yingjie Chen Lei Wang Guixia Liu Weihua Li Yun Tang

Structure-based prediction for the site of metabolism (SOM) of a compound metabolized by human cytochrome P450s (CYPs) is highly beneficial in drug discovery and development. However, the flexibility of the CYPs' active site remains a huge challenge for accurate SOM prediction. Compared with other CYPs, the active site of CYP2A6 is relatively small and rigid. To address the impact of the flexib...

2001
Shigehiko Kanaya Makoto Kinouchi Takashi Abe Yoshihiro Kudo Yuko Yamada Tatsuya Nishi Hirotada Mori Toshimichi Ikemura

With increases in the amounts of available DNA sequence data, it has become increasingly important to develop tools for comprehensive systematic analysis and comparison of species-specific characteristics of protein-coding sequences for a wide variety of genomes. In the present study, we used a novel neural-network algorithm, a self-organizing map (SOM), to efficiently and comprehensively analy...

2000
Jouko Lampinen Timo Kostiainen

The Self-Organizing Map, SOM, is a widely used tool in exploratory data analysis. Visual inspection of the SOM can be used to list potential dependencies between variables, that are then validated with more principled statistical methods. In this paper we discuss the use of the SOM in searching for dependencies in the data. We point out that simple use of the SOM may lead to excessive number of...

2002
Victor-Emil Neagoe Armand-Dragos Ropot

We present a new neural classification model called Concurrent Self-Organizing Maps (CSOM), representing a winner-takes-all collection of small SOM networks. Each SOM of the system is trained individually to provide best results for one class only. We have considered two significant applications: face recognition and multispectral satellite image classification. For first application, we have u...

Journal: :Inf. Sci. 2004
Huidong Jin Wing-Ho Shum Kwong-Sak Leung Man Leung Wong

The Self-Organizing Map (SOM) is a powerful tool in the exploratory phase of data mining. It is capable of projecting high-dimensional data onto a regular, usually 2dimensional grid of neurons with good neighborhood preservation between two spaces. However, due to the dimensional conflict, the neighborhood preservation cannot always lead to perfect topology preservation. In this paper, we estab...

Journal: :Water science and technology : a journal of the International Association on Water Pollution Research 2013
Ying-Heng Fei Xiao-Yan Li

The effect of decomposition and diagenesis of sediment organic matter (SOM) on the adsorption of emerging pollutants by the sediment has been seldom addressed. In the present experimental study, artificial sediment was incubated to simulate the natural organic diagenesis process and hence investigate the influence of organic diagenesis on the adsorption of tetracyclines (TCs) by marine sediment...

2014
Ozlem Ozbudak Zümray Dokur

Protein fold classification is an important problem in bioinformatics and a challenging task for machine-learning algorithms. In this paper we present a solution which classifies protein folds using Kohonen’s Self-Organizing Map (SOM) and a comparison between few approaches for protein fold classification. We use SOM, Fisher Linear Discriminant Analysis (FLD), K-Nearest Neighbour (KNN), Support...

2005
Fernando C. LOURENÇO Victor S. LOBO Fernando L. BAÇÃO

This paper describes the application of the Self-Organizing Map (SOM) in visual exploration of physical geography data. The main justifications for the application of SOM in this issue is that its stresses local factors and topological order. Public domain thematic maps from Portuguese Environment Institute are used. An adequate geospatial unfolding of SOM is presumed to assist a better represe...

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