The weights, activation function, and set of input values for a Neural Network are given below:                                                                                                                     Weights: w1 = 2, w2 = -3, w3 = 4, w4 = -2, w5 = 5                   1 when p > 0                   Activation function: f (p) =     0 when p = 0     , where p is weighted sum of inputs                   -1 when p < 0                  Set of input values (Set S1, S2, S3 and input values x1, x2, x3, x4, x5):             S1 S2 S3 x1 2 4 1 x2 3      2 3 x3 3 6 -2 x4 -4 -3 3 X5 -3 -2 3                What is the final output value for each set of input values?

Q: l neural networks we use activation functions. Explain why you would select on activation function…

A: What are activation functions? To answer the question of what Activation Functions are, let’s first…

Q: Design a Turing machine that decides the language above by giving a high-level description of how it…

A: Turing machine:   As an illustration, The string of 0s and 1s is handled by a Material object, with…

Q: An edge from process Pi to Pj in a wait for graph indicates that : a. Pi is waiting for Pj to…

A: Question An edge from process Pi to Pj in a wait for graph indicates that : a. Pi is waiting for Pj…

Q: Compute a dominator tree for the control flow graphs given below

A: A dominator tree is a tree structure that represents the dominance relationships between nodes in a…

Q: Implement the perceptron rule for the set of input training vectors X1= X2= 0 -1.5 0.5 1 Initial…

A: Note : Answering the question in python as no programing language is mentioned. Task : Given the…

Q: Draw a picture of the graph G=)V, E), where V-{a, b, c, d, e}, E={e_1, e_2, e_3, e_4, e_5, e_6}, and…

A: We need to draw a graph of the given vertices and edges of the graph. The vertices are- V =…

Q: Q2: Find the (n) & (a) of neuron: ifn0 out-0 X1 X2 XI 0.9 1 0.6 0.8 0.9 Σ X2 0.9 0.7 B-05

A: Gernal Formula,

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: Find the dimensions and outputs of the expressions w1,w2,w3,b1,b2,b3 in the given neural network a…

A: Given : Neural network with whole architecture. Task : Dimensions of w1,w2,w3,b1,b2,b3

Q: 01/ Given the following description of a Perceptron: w1=6, w2=-3, b=-4 and the threshold function…

A: It is defined as the piece of a computing system designed to simulate the way the human brain…

Q: Consider the following statements regarding weight initialisation in neural networks: A: It is…

A: According to the information given:- We have to choose the correct option to satisfy the statement…

Q: An artificial neural network consists of only two layers. Three neurons are in the input layer and…

A: Given, Weights, w1=0.1, w2=0.1, w3=0.1 Inputs, x1=9.0, x2=6.0, x3=1.0 Desired output = 0 Learning…

Q: Consider a neuron with a sigmoidal activation function. The input vector (x1,x2]=[1,1] and the…

A: Given: The neuron is having sigmoidal activation function. The input vector = [1, 1] The weights are…

Q: The loop invariant is y=ax for loop segment given below. Identify the strongest post- condition if…

A: Here is the explanation of above to find the postcondition and precondition. See below steps.

Q: Consider a neuron with 3 inputs, 1 output, and a threshold (=0) activation function. If the two…

A: Consider a neuron with 3 inputs, 1 output, and a threshold (=0) activation function. If the two…

Q: 1. What does a neuron compute? A neuron computes an activation function followed by a linear…

A: Neuron A mathematical function called a neuron simulates the operation of a biological neuron. The…

Q: X₁=2, X₂=1, W₁=0,5, w₂=1.2, W3=2, W4=0,8, W5-0,7, w6-0,8 b₁=1, b₂=1 y=? (Sigmoid Fonction) Input X₁…

A: ANNs are a type of computational model inspired by the structure and function of the human brain,…

Q: A neuron with 4 inputs has the weight vector w = [1,2,3,4] and a bias 0 = 0 (zero). The activation…

A: Actually, given information A neuron with 4 inputs has the weight vector w = [1; 2; 3; 4] and a…

Q: Write Top down approach Algorithm in Unsupervised Learning Input: I = {I1, I2, … , In} Output: O

A: Introduction : The top-down approach, also known as a “Top-down design”, is a design methodology…

Q: 1. What does a neuron compute? A neuron computes an activation function followed by a linear…

A: Artificial Neural Network: A computational model known as an artificial neural network (ANN)…

Q: Apply the backpropagation algorithm to the neural network given below. Find the weights after the…

A:

Q: Consider the back propagation neural network as shown in figure 1, assume that the neurons have a…

A: a) Forward pass : y = 0.641b) Reverse passy′ =…

Q: the inference technique used is: a. Forward chaining b. Backward chaining

A: By using forward chaining,we assume fact/database  in A1,A2,A4 . SOLUTION:

Q: Let x, y, z be positive integers (x, y, z> 0) represented in unary. Assume that x> z. Design a…

A:

Q: 8) A neural network with 3 inputs and their respective weights are given below. What will be the…

A: Neural networks are computational models inspired by the human brain, designed to recognize patterns…

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

A: Here is the diagram of the problem. See below steps.

Q: With the following information about a Turing Machine (automata): Q = { q0, q1 } Σ = { a, b }, Γ= {…

A: Given Information : States : q0 , q1 Alphabets = {a,b} Machine Symbols = { a, b, ◻︎ } Final State =…

Q: Draw a neural network (including structure, weights and thresholds) that computes the majority…

A: Solution  #Use python to build a neural network: import numpy, random, os#package learnr = 1…

Q: Perform the Adaline Algorithm of Neural Network. Explicitly write down the sequence of steps.

A: The Adaline Algorithm of Neural Network is-

Q: 1. What does a neuron compute? A neuron computes an activation function followed by a linear…

A: I have given answer below with each option explanation.

Q: Consider a neuron with a sigmoidal activation function. The input vector [x1,x2]=[1,1] and the…

A: First of all, remember that when an input is given to the neural network, it returns an output. On…

Q: Consider a neuron with 2 inputs, 1 output, and a threshold activation function. If the two weights…

A: ANSWER :  GIVEN THAT :

Q: 1. What does a neuron compute? A neuron computes an activation function followed by a linear…

A: I have given explanation in the below steps.

Q: The cost function of a general neural network is defined as J(ŷ,y) 1 m L(VW), y() The loss function…

A: The solution is given below:

Q: Artificial neural networks (ANNs) are computational models that are inspired by the structure and…

A: Understanding Artificial Neural Networks Artificial Neural Networks (ANNs) are indeed computational…

Q: Exactly what kind of calculations does a neuron perform? The activation function is calculated…

A: In artificial neural networks, a neuron is a mathematical function that takes one or more input…

Q: Consider the back propagation neural network as shown in figure 1, assume that the neurons have a…

A: Alright, let's break this down step by step.Given the figure and the information provided, let's…

Q: Artificial neural networks (ANNS) are computational models that are inspired by the structure and…

A: Artificial Neural Networks (ANNs) are computing systems vaguely inspired by the biological neural…