A) Describe in details how Neural Network work. Make sure to show how to calculate the...
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?
Homework Answers
ADVANTAGES OF NEUTRAL NETWORK:
- It stores the information on the entire network
- It has the ability to work with incomplete knowledge of data
- It has the ability to make machine learning of learning new skills
- In Neural networks it can do multiple jobs at the same time
DISADVANTAGES OF NEUTRAL NETWORK:
- As the neutral network do the processing with parallel power so because of that realization of the equipment is dependent.
- The ANN problem as without giving any alert it reduces the trust of the network.
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Add Answer to:
A) Describe in details how Neural Network work. Make sure to
show how to calculate the...
Calculate the output of the network given the following neural network: Weights between input and...
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
Calculate the output of the network given the following neural network: Weights between input and hidden...
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...
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...
Draw a fully connected neural network with 1 hidden layer where the number of units input, hidden layer, and output layer are 3, 2, 1, respectively. . (5+5+5+5) a. Show all the weight matrices a...
Draw a fully connected neural network with 1 hidden layer where the number of units input, hidden layer, and output layer are 3, 2, 1, respectively. . (5+5+5+5) a. Show all the weight matrices and their dimensions for this neural network. b. Label the network connections using the weight values (e.g., w12, w23). c. Total how many weights do you need to train in this neural network? . Explain supervised and unsupervised learning in your own words. (10)
Draw a...
1. Consider a neural network, which contains one hidden layer and an output layer with one...
1. Consider a neural network, which contains one hidden layer and an output layer with one output unit. Let the hidden units have negative sigmoid as the activation function, which is formulated as 1 n(v) 1 + exp(-1) and the output unit has a linear activation function in which the output is equal to the activation input). (a) Show that the derivative of the negative sigmoid obeys the following relation dn(v) dv = n(v)(1 + n(v)) (b) Let the cost...
4.7. Consider a two-layer feedforward ANN with two inputs a and b, one hidden unit c, and one output unit d. This net...
4.7. Consider a two-layer feedforward ANN with two inputs a and b, one hidden unit c, and one output unit d. This network has five weights (wca, Wcb, Wco, Wse, Wao). where wro represents the threshold weight for unit x. Initialize these weights to the values (.1,.1,.1,.1,.1), then give their values after each of the first two training iterations of the BACKPROPAGATION algorithm. Assume learning rte '-.3, momentum α-: 0.9, incremental weight updates, and the following training examples: 0 1...
2) if any alpha or beta show work 3)Here,make sure to describe how many reducing groups are in the molecule dissaccha...
2) if any alpha or beta show work
3)Here,make sure to describe how many reducing groups are in
the molecule dissaccharide.SHOW Work
Sugar Structures Describe the common structural features and the differences for each pair: (a) cellulose and glycogen; (b) D-glucose and D-fructose; (c) maltose and sucrose. Reducing Sugars Draw the structural formula for a-D-glucosyl-(1-6)-D-mannosamine and circle the part of this structure that makes the compound a reducing sugar.
Find Ix and Vx in the network in Figure 4. make sure you show your work....
Find Ix and Vx in the network in Figure 4. make sure you show your work. 4 ΚΩ 10 ΚΩ + 10V 20V(+ (+2Vx 6 ΚΩ 1, 10 kΩ Figure 4
Calculate tan (4) as an exact value. Make sure to show all your work including a...
Calculate tan (4) as an exact value. Make sure to show all your work including a drawing of the angle and the triangle.
make sure not to copy previous work For the frame shown below: 1- Calculate the reactions at the supports 2- Show the equilibrium at nodes B and C 3- Draw the normal force, the shear force and the...
make sure not to copy previous work
For the frame shown below: 1- Calculate the reactions at the supports 2- Show the equilibrium at nodes B and C 3- Draw the normal force, the shear force and the bending moment diagrams 2 KN 3 KN 2 m 2 m 3 m 4 m
For the frame shown below: 1- Calculate the reactions at the supports 2- Show the equilibrium at nodes B and C 3- Draw the normal force, the...
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...
Draw a fully connected neural network with 1 hidden layer where the number of units input, hidden layer, and output layer are 3, 2, 1, respectively. . (5+5+5+5) a. Show all the weight matrices and their dimensions for this neural network. b. Label the network connections using the weight values (e.g., w12, w23). c. Total how many weights do you need to train in this neural network? . Explain supervised and unsupervised learning in your own words. (10)
Draw a...
1. Consider a neural network, which contains one hidden layer and an output layer with one output unit. Let the hidden units have negative sigmoid as the activation function, which is formulated as 1 n(v) 1 + exp(-1) and the output unit has a linear activation function in which the output is equal to the activation input). (a) Show that the derivative of the negative sigmoid obeys the following relation dn(v) dv = n(v)(1 + n(v)) (b) Let the cost...
4.7. Consider a two-layer feedforward ANN with two inputs a and b, one hidden unit c, and one output unit d. This network has five weights (wca, Wcb, Wco, Wse, Wao). where wro represents the threshold weight for unit x. Initialize these weights to the values (.1,.1,.1,.1,.1), then give their values after each of the first two training iterations of the BACKPROPAGATION algorithm. Assume learning rte '-.3, momentum α-: 0.9, incremental weight updates, and the following training examples: 0 1...
2) if any alpha or beta show work
3)Here,make sure to describe how many reducing groups are in
the molecule dissaccharide.SHOW Work
Sugar Structures Describe the common structural features and the differences for each pair: (a) cellulose and glycogen; (b) D-glucose and D-fructose; (c) maltose and sucrose. Reducing Sugars Draw the structural formula for a-D-glucosyl-(1-6)-D-mannosamine and circle the part of this structure that makes the compound a reducing sugar.
Find Ix and Vx in the network in Figure 4. make sure you show your work. 4 ΚΩ 10 ΚΩ + 10V 20V(+ (+2Vx 6 ΚΩ 1, 10 kΩ Figure 4
Calculate tan (4) as an exact value. Make sure to show all your work including a drawing of the angle and the triangle.
make sure not to copy previous work
For the frame shown below: 1- Calculate the reactions at the supports 2- Show the equilibrium at nodes B and C 3- Draw the normal force, the shear force and the bending moment diagrams 2 KN 3 KN 2 m 2 m 3 m 4 m
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