Assignment 4.pdf 2/3 In this question you will experiment with a simple recurrent neural network, where you will try to model a sinusoidal function with noise, whose amplitude becomes larger and larger as the independent variable t increases (0sis N ). This function can be expressed in Python as x=(np.sin(0.02*t)+2*np.random.rand(N))*(t/N) . For N=5000 we have: 2.5 2.0 15 10 0.5 0.0 -0.5 -1.0 1000 2000 3000 4000 5000 The idea is that you will train a recurrent neural network with points up to a certain value, Tp. This is all the training points will be is Tp. The length of the sequence provided to the network is a parameter that you can tune You will use the notebook provided for this question named "A4Q3.ipynb" a) Complete the notebook provided to fulfill this task. You need to add at least one simpleRNN layer and a proper output layer. b) Starting with length = 4, discuss how different choices of the length of the sequence fed to the network can have an impact on performance. + c) Discuss how different network architectures can have an impact on performance. Note 1: for simplicity, don't change the values of the variables / and Tp. Note 2: make sure you understand the code before addressing these questions