Untitled Deck Flashcards

1
Q

What is the primary biological inspiration for artificial neural networks?

A

The brain, which consists of approximately (10^{11}) neurons, (10^{14}) synapses, and has a response time of 1–10 ms.

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2
Q

What is the main challenge of traditional solutions in robotics?

A

They require exhaustive knowledge of the mechanical characteristics of the robot and careful calibration.

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3
Q

Who proposed the McCulloch-Pitts model?

A

McCulloch and Pitts in 1943.

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4
Q

What are the key components of artificial neurons?

A

Synaptic weights, threshold, synaptic potential, activation function, and state.

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5
Q

What are the main types of neuron states?

A

Discrete (binary or bipolar) and continuous.

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6
Q

Name three types of activation functions.

A

Step, ramp, and exponential functions.

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7
Q

What is a perceptron primarily used for?

A

Recognition and classification tasks.

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8
Q

Who introduced the concept of a single-layer perceptron?

A

Frank Rosenblatt in 1958.

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9
Q

What is a significant limitation of single-layer perceptrons?

A

They can only classify linearly separable sets.

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10
Q

How did Minsky and Papert demonstrate the limitation of perceptrons in 1969?

A

By showing they cannot implement the XOR function.

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11
Q

What is the primary solution to overcome the limitations of single-layer perceptrons?

A

Adding more layers to create a multilayer perceptron.

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12
Q

What is the purpose of the backpropagation algorithm in multilayer perceptrons?

A

To find synaptic weights that minimize the error.

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13
Q

What are the main types of layers in a neural network?

A

Input, hidden, and output layers.

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14
Q

What are the types of synapses in artificial neural networks?

A

Forward, backward, and lateral synapses.

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15
Q

Define feed-forward neural network architecture.

A

An architecture where connections between the nodes do not form a cycle.

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16
Q

What is a recurrent neural network?

A

A network where connections can form cycles, allowing it to retain memory over time.

17
Q

What are radial basis functions (RBF) typically used for?

A

Function approximation, time series prediction, and classification.

18
Q

Who introduced RBF networks?

A

Broomhead and Lowe in 1988.

19
Q

What is the most commonly used distance metric in RBF networks?

A

Euclidean distance.

20
Q

Give an example of a popular radial basis function.

A

The Gaussian function: (phi(r) = exp(-(epsilon r)^2)).

21
Q

What are the two main phases in training RBF networks?

A

Selection of RBF centers and computation of synaptic weights.

22
Q

What is a critical step during the training of RBF networks?

A

Selecting RBF centers to match the distribution of training data.

23
Q

Name one method used to compute synaptic weights in RBF networks.

A

Gradient descent.

24
Q

What is the advantage of multilayer perceptrons in solving inverse kinematics problems?

A

They do not require precise mechanical knowledge and adapt to variations.

25
Q

What does the activation function do in an artificial neuron?

A

It determines the output state based on the input synaptic potential.

26
Q

What is the role of the threshold in an artificial neuron?

A

It sets a value above which the neuron activates.

27
Q

What is meant by ‘adaptive synapses’ in artificial neural networks?

A

Synapses that adjust their weights during learning.

28
Q

Why are neural networks considered robust and fault-tolerant?

A

Because information is distributed and they can continue functioning despite partial damage.

29
Q

What is online learning in the context of neural networks?

A

A learning approach where the model updates continuously as new data arrives.

30
Q

What is the significance of batch learning in neural networks?

A

The model updates after processing a batch of training data, reducing the frequency of updates.