Kohonen Self Organizing Map Used Cluster Four Vectors Let Vectors Clustered 1 1 0 0 0 0 0 Q43808179
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A Kohonen self-organizing map is used to cluster four vectors.Let the vectors to be clustered be(1,1,0,0);(0,0,0,1);(1,0,0,0);(0,0,1,1)
The maximum number of clusters to be formed is m = 2. Supposethe learning rate is η = 0.6, The neighborhood of node J is set sothat only one cluster updates its weights at each step (R = 0).Initial weight matrix is
3. A Kohonen self-organizing map is used to cluster four vectors. Let the vectors to be clustered be (1,1,0,0); (0,0,0,1); (1,0,0,0);(0,0,1,1) The maximum number of clusters to be formed is m = 2. Suppose the learning rate is n = 0.6, The neighborhood of node J is set so that only one cluster updates its weights at each step (R = 0). Initial weight matrix is 0.2 0.8 0.6 0.4 0.5 0.7 0.9 0.3 (a) Calculate the updates in the weight matrix after training the network using the first vector (1, 1, 0, 0). [5 marks] (b) Write a Matlab program to (1) load these input vectors; (2) create a Self- Organizing Map; (3) train the Network; (4) view the Network; (5) plot results using different SOM plots. [5 marks] Show transcribed image text 3. A Kohonen self-organizing map is used to cluster four vectors. Let the vectors to be clustered be (1,1,0,0); (0,0,0,1); (1,0,0,0);(0,0,1,1) The maximum number of clusters to be formed is m = 2. Suppose the learning rate is n = 0.6, The neighborhood of node J is set so that only one cluster updates its weights at each step (R = 0). Initial weight matrix is 0.2 0.8 0.6 0.4 0.5 0.7 0.9 0.3 (a) Calculate the updates in the weight matrix after training the network using the first vector (1, 1, 0, 0). [5 marks] (b) Write a Matlab program to (1) load these input vectors; (2) create a Self- Organizing Map; (3) train the Network; (4) view the Network; (5) plot results using different SOM plots. [5 marks]
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