Please show the work and answer for the following problem in the photo below.
The above neural network represented following function
Above given neural network has 4 nodes totally
1st node ==> -1.5 bias is added
2nd node ==> -0.5 bias is added
3rd node ==> -0.5 bias is added
4th node ==> -0.5 bias is added
Output @ 1st node = x1 + x2 - 1.5
Output @ 2nd node = x1 + x2 - 0.5
Output @ 3rd node = (x1 + x2 - 1.5) * -1 + (x1 + x2 - 0.5)*1 - 0.5
Output @ 4th node = [ (x1 + x2 - 1.5) * -1 + (x1 + x2 - 0.5)*1 - 0.5 ] * -1 + 0
Final output = [ (x1 + x2 - 1.5) * -1 + (x1 + x2 - 0.5)*1 - 0.5 ] * -1
Please show the work and answer for the following problem in the photo below. Neural Network...
ARTIFICIAL NEURAL NETWORK HELP PLEASE Compute the output value for the neural network shown below. The artificial neural network has two inputs, two neurons in the hidden layer 1, one neuron in the output layer and one output. Suppose that the artificial neural network is using the logsig function A). manually and B). using neural lab code in C Answer should be z = 0.641199 Please answer BOTH A and B AND show FULL work LAYER 1 LAYER 2 Neo...
A) Describe in details how Neural Network work. Make sure to show how to calculate the value of nodes in output layer in the feedforward step, and how to update weights between output layer and hidden layer, and weights between input and hidden layer. Show all the involved formula in the steps. What are the advantages and disadvantages of Neural Network?
Calculate the output of the network given the following neural network: Weights between input and hidden layer are as follows: w11 = 1.2 w12 = 1.5 w21 = 1.5 w22 = 2.0 w31 = 2.0 w32 = 1.0 Weights between input and hidden layer are as follows: w11 = 1.5 w21 = 2.1 Inputs are: x1 = 0.7 x2 = 0.9 x3 = 0.1
A deep learning problem. The following matrices describing a neural network were uncovered by scientists. The weights for the hidden layer are given in the matrix W[1] = [0 1] The bias for the hidden layer is given in the vector b[1] = [1] The weights for the output layer are given in the vector W[2] [8] 0 1 The biases for the output layer are 612] = -0.5 0.75 The input X is given in the vector X 1.25...
Calculate the output of the network given the following neural network: Weights between input and hidden layer are as follows: w11 = 1.2 w12 = 1.5 w21 = 1.5 w22 = 2.0 w31 = 2.0 w32 = 1.0 Weights between input and hidden layer are as follows: w11 = 1.5 w21 = 2.1 Inputs are: x1 = 0.7 x2 = 0.9 x3 = 0.1
1. Compared with PID Control, what are the advantages and disadvantages of Neural Network Control? 2. The multi-layer neural network shown in Figure I has two inputs and one output. The network has two neurons in a hidden layer. The network is to be trained with backpropagation algorithm. Each neuron has a sigmoid activation function: Assume that the biases to the neurons is +1 and the learning rate is 1. The network has the following initial weights: (w). w1 wa1...
Neural Networks We will now build some neural networks to represent basic boolean functions. For simplicity, we use the threshold function as our basic units instead of the sigmoid function, where threshold(t) +1 if the input is greater than 0, and 0 otherwise, we have inputs xi (+1, 0) and weights yī (possible values-l, 0, 1). Suppose we are given boolean input data xi where 1 represents TRUE and 0 represents FALSE. The boolean NOT function can be represented by...
Q8: (8 marks) [basic design problem] Given below is a single node in a neural network. Supposing that d is 4, x={4,2,5,2), and w={0.2,0.3.0.4,0.1), b=0.1, and that the activation function is a standard ReLU, that is =max(0.x), where x is the input to the activation function. b W1 W X 1 Xd (a) What is the output of this node? [2 marks]
Please answer the problem below for all parts . Please show all work and write clearly. The answers are below, but work must be shown to get to the answers. Thanks. answers 8.14. Design a second-order digital bandpass Chebyshev filter with the following specifications: Center frequency of 1.5 kHz Bandwidth of 200 Hz 0.5 dB passband ripple Sampling frequency of 8,000 Hz a. Determine the transfer function and difference equation. 8.14 a. 0.1815-0.1815z2 1-0.6265z +0.6370z y(n)-0.1815x(n)-0.1815x(n-2)+0.6265y(n1) 0.6370y(n-2) 8.14. Design a...
Information in the neural network diagram below has been provided to enable you answer the questions that follows. Hidden Layer Output Layer Input Layer 0.05 N3=? Input] =02 — Inputl =0.2 01 -0.015 0.2 0.01 02 conX 003: 0.01 -0.015 N-?.005 N4=? 0.05 - No? - N6=? 0.01 0.015 Input2 =0.9— (2 0.9 0.02 0.05 -0.01 5 N5=? Using logistic function, compute the output of the neurons in the hidden layer and output layer. (15pts.) i) Neuron3 (N3) ii) Neuron4...