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second self-organizing map

Maximal Ratio Combining using Self Organizing Map in Wireless Channels

Maximal Ratio Combining using Self Organizing Map in Wireless Channels

... We have used two SOM units for the design of the equaliser. The first unit called SOM(S) classifies the patterns due to the contributions from the significant channel coefficients while the second unit called ...

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Landforms identification using neural network-self organizing map and SRTM data

Landforms identification using neural network-self organizing map and SRTM data

... and second, provide a controlling boundary condition for actual geomorphic processes (Dehn et ...arc second (~ 90 m) for all areas and 1 arc second (~ 30 m) for the United States ...

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Increasing the lifetime of wireless sensor networks by Self-Organizing Map algorithm

Increasing the lifetime of wireless sensor networks by Self-Organizing Map algorithm

... the second stage (400 nodes) m =80 or m =50 Also, we assume are specified that the values of the coefficients of the cost function based on the importance of selecting cluster heads to trial the decision ...

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Lifestyle patterns in the Iranian population: Self- organizing map application

Lifestyle patterns in the Iranian population: Self- organizing map application

... The Global Physical Activity Questionnaire was used for assessing physical activity in 3 main domains of work- related activity, recreational activity, and walking (11). The questions about diet were designed based on ...

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Creation of Text Document Matrices and Visualization by Self-Organizing Map

Creation of Text Document Matrices and Visualization by Self-Organizing Map

... SOM is presented in Fig. 4. We also see clusters that correspond to the classes. Only the cluster, corresponding to the first class, splits into two subclusters. Probably, not all the first five words in the dictionary ...

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Software Reusability Classification and Predication Using Self Organizing Map (SOM)

Software Reusability Classification and Predication Using Self Organizing Map (SOM)

... the second step was using supervised Back propagation Neural Network (BPNN) and fuzzy inference rules applied on CK metric values to categorize the data into Very Low, Low, Medium, High and Very High reusability ...

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Self Organizing Map Approach for Identifying Mental Disorders

Self Organizing Map Approach for Identifying Mental Disorders

... The second data set is the cross validation which is used usually to compute the error in a test data set at the same time that the network is being ...feature map generated by the unsupervised (Kohonen) ...

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NOISY IMAGE SEGMENTATION USING A SELF-ORGANIZING MAP NETWORK

NOISY IMAGE SEGMENTATION USING A SELF-ORGANIZING MAP NETWORK

... Although normal SOM has sufficient result through its features such as learning capability from examples, generalization ability, and non- parametric estimation, it suffers from two main problems. First, it is highly ...

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The Time Adaptive Self Organizing Map for Distribution Estimation

The Time Adaptive Self Organizing Map for Distribution Estimation

... distribution. Then it changes to Exponential, then Rayleigh, and finally Laplacian distributions. In fact, the TASOM network used in this experiment undergoes a very changing environment, which endure five complete ...

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SELF ORGANIZING MAP BASED CLUSTERING MODEL BY ANALYZING EIGEN SYSTEM OF PCA

SELF ORGANIZING MAP BASED CLUSTERING MODEL BY ANALYZING EIGEN SYSTEM OF PCA

... the second method is consuming less space and computation time than the ...the second method is computationally more efficient than the first for clustering of the wine ...

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Integrative Self Organizing Map—A Mean Pattern Model

Integrative Self Organizing Map—A Mean Pattern Model

... The proposed iSOM is composed of two major steps. In the first step, the vector of all differential expression matrices across multiple data sets is analyzed using SOM leading to an array in which each neuron represents ...

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Social Interaction and Self-Organizing Map

Social Interaction and Self-Organizing Map

... rates. Second, the strong class boundaries were traced back to the important events or incidents which occurred in the ...the second period was due to the revision of regulation law for ...

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Hand Gesture Recognition System Using Kohonen Self Organizing Map

Hand Gesture Recognition System Using Kohonen Self Organizing Map

... There are three phases in the development of the system as shown in Fig. 7. First is the training phase, second is setting boundaries, and third is the testing phase. In the training phase, ten samples of each ...

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Application of Self Organizing Map for Exploration of REEs’ Deposition

Application of Self Organizing Map for Exploration of REEs’ Deposition

... metasomatic aureole differs widely. The orebody is hosted by volcanic members (intrusive and extrusive alkali rhyolites) of the epicontinental to continental Infracambrian Esfordi Formation [17]. The orebody and the me- ...

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Image Fusion Using Self Organizing Feature Map With Histogram Equalization

Image Fusion Using Self Organizing Feature Map With Histogram Equalization

... on self organizing feature map (SOFM) with histogram ...The self organizing feature map with histogram equalization produces numerous slices of the source and reference images ...

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INTERACTING THROUGH DISCLOSING: PEER INTERACTION PATTERNS BASED ON 
SELF DISCLOSURE LEVELS VIA FACEBOOK

INTERACTING THROUGH DISCLOSING: PEER INTERACTION PATTERNS BASED ON SELF DISCLOSURE LEVELS VIA FACEBOOK

... the Self- Organizing Map Algorithm (SOM) in ...the self-organized map, an architecture suggested for artificial neural networks, is explained by presenting simulation experiments and ...

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Enhanced self organizing map with particle swarm optimization for classification problems

Enhanced self organizing map with particle swarm optimization for classification problems

... The performance of standard SOM, ESOM, SOMPSO and ESOMPSO using various distance measures: Euclidean distance, Manhattan distance, and Chebyshev distance, are evaluated and compared. [r] ...

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An Application of Partitive Clustering Algorithm for Landslide Hazard Zonation

An Application of Partitive Clustering Algorithm for Landslide Hazard Zonation

... and Self-Organizing Map Algorithms in Artificial Neural Network to map landslide hazard areas using the datasets of eight causative landslide indicators such as slope gradient, vertical ...

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Image Compression using Neural Network

Image Compression using Neural Network

... Growing Self Organizing Map algorithm, which exhibits a clear-cut idea on application of multilayer perceptron with special features compare to Hoffman ...

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Mining hidden information from library databases using SOM (Self Organizing Map)

Mining hidden information from library databases using SOM (Self Organizing Map)

... (Self Organizing Map) on SOM (Self Organizing Map) Algorithm to Order Documents Algorithm to Order Documents Based on Their Full Text ...

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