Study the scenario and answer the question. * 0.2 A WA,B=0.2 0.8 B AB=0.4 Assume that B is an intermediate node of a neural network, the forward propagation values of nodes A and B are 0.2 and 0.3; the associated error AB of node B that was computed by the back propagation algorithm is 0.4, the learning rate y is assume to be 0.5. How does the backpropagation algorithm update the weight WA, B of the edge that connects node A and B? What is the new value of weight WA,B?

Q: X2 W13.38 1.13, w23 -1.08 -.56 W24 XOR Gate WIL (14) -1.49- کہانیا -.46 -.23 output

A: This exercise is an introduction to using the FEED FORWARD and BACK PROPOGATION algorithm for the…

Q: Suppose that we use sigmod activation function and square loss function: (t- o)2. The learning rate…

A: In neural networks, gradient descent is used to train the network by minimizing the loss function.…

Q: A multi-layer neural network has its weight as below. All neurons use linear activation function.…

A: We need to calculate MSE loss of the neural network. In the below steps Mse calculation is given.

Q: Prove the updating equation for the Backpropagation:

A: Prove the updating equation for the Backpropagation:

Q: )1. Consider the neural network in Figure 25.13. Let bias values be fixed at 0, and let the weight…

A: Here is the answer:-

Use of XOR function

XOR function or exclusive OR function was introduced in Excel 2013. This function is available under excel logical functions. For the given statement, the XOR function will return true only when either of the statements is true. It returns false when both the statements are true or when both the statements are false.