Machine Learning- Neural Networks Project

Single Hidden Layer Neural Network Models and the Sigmoid Function is used for the separation of classes. 1) Design and program the algorithm for solution of the problem. 2) Do not use the function is ready to solve the problem(not use libraries, setting up the algorithm is important). Write the code yourself. 3) Calculate the values ??of the appropriate weight for classification. Decision Boundary Vector for N1 neuron: w10+w11*x1+w12*x2=0 Decision Boundary Vector for N2 neuron: w20+21*x1+w22*x2=0 Draw these decision boundary vectors. 4) Select 5 samples in the training set. For these examples V1 (x1, x2) and V2 (x1, x2) outputs selected samples along this axis as the axis using the mark. To obtain the decision boundary vector for N3. We have got the training dataset's picture. This project's deadline is 13 December 2012. This must be finished urgent.