Consider the single layer perception given below:
Obtain the output for each of the following input pattern:
| Patterns | p1 | p2 | p3 | p4 |
| x1 | 1 | 0 | 1 | 1 |
| x2 | 0 | 1 | 0 | 1 |
| x3 | 0 | 1 | 1 | 1 |
The given pattern is represented by a single-layer perceptron (SLP). In a single-layer perceptron, each input is multiplied by its corresponding weight, and the sum of these products is passed through an activation function to obtain the output. Assuming binary threshold activation function, where the output is 1 if the sum is greater than or equal to 0, and 0 otherwise, ______ ___ _______ __________ _________ _________.
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Find the length and order of the following schema:
i) S1 =1** 0 0 *1* *
ii) S2 = *0 0 *1 * *
iii) S * * * 0 * * * *
iv) S4 = *1 * 0 1 *
Solve the network to approximate the function:
g(x)=1+sin
for −1≤ x ≤ ,1 choosing the initial weights and bias as the random numbers.
Consider the single layer perception given below:
Obtain the output for each of the following input pattern:
| Patterns | p1 | p2 | p3 | p4 |
| x1 | 1 | 0 | 1 | 1 |
| x2 | 0 | 1 | 0 | 1 |
| x3 | 0 | 1 | 1 | 1 |
Determine the fuzzy relation T as a composition between the fuzzy relations R and S given below by using max-min and max-product:
Implement AND function using McCulloch-Pitts neuron.
Computer the output for the neurons in the kohonen networks, the related data is given below:
i) Input to Kohnen neural network:
Input Neuron-1` (I1) =0.5
Input Neuron-2 (I2) =0.75
ii) Connected weights between the neurons are as given below:
I O 1.0:
1 → 1
I O 2.0:
2 → 2
I O 3.0:
1 → 2
I O 4.0
Verify whether the Genetic Algorithm (GA) improves the solution from one generation to the next generation, for the function given below:
Maximize:
f(x) =
Subject to:
1≤ x ≤16
Assume that chromosomes of length 6 are created at random and modified by Roulette-Wheel selection.