HISTORY
Who proposed the first mathematical model of an artificial neuron in 1943?
McCulloch and Pitts
What is the basic processing unit of a neural network?
Neuron
What does TLU stand for?
Threshold Logic Unit
What is the main purpose of the perceptron learning algorithm?
To adjust weights for correct classification
Multi-Layer Perceptron
What does MLP stand for?
Who introduced the Perceptron in 1957?
Frank Rosenblatt
What are the three main components of an artificial neuron?
Inputs, Weights, Activation Function)
What is the output of a perceptron when the weighted sum exceeds the threshold?
1
What parameter is updated during perceptron learning?
Weights
Which layer lies between input and output layers in an MLP?
Hidden Layer
Which decade is considered the birth of Artificial Intelligence as a formal field?
1950
What is the role of the activation function?
Introduces non-linearity / decides output
Can a single-layer perceptron solve the XOR problem?
NO
What is the learning rule used in perceptron training called?
Error Correction Learning Rule
Which algorithm is commonly used to train MLPs?
Backpropagation
What event led to the first "AI Winter"?
Limitations of Perceptrons and reduced funding
What is the mathematical operation performed before activation?
Weighted Sum
What type of problems can a single-layer perceptron solve?
Linearly Separable Problems
What happens to the weights when a sample is misclassified?
Weights are adjusted/updated
Why are hidden layers important in MLPs?
To learn complex non-linear relationships
What development revived interest in neural networks in the 1980s?
Backpropogation
What biological structure inspired artificial neurons?
Human Brain Neurons
Write the output equation of a perceptron.
y = f(Σwᵢxᵢ + b)
Write the perceptron weight update rule.
w(new) = w(old) + η(t−y)x
Why is an MLP called a Universal Function Approximator?
It can approximate any continuous function given enough neurons and layers