Huawei Exam H13-311_V3.5 Topic 4 Question 8 Discussion

Actual exam question for Huawei's H13-311_V3.5 exam

Question #: 8
Topic #: 4

Which of the following statements is false about feedforward neural networks?

AA unidirectional multi-layer structure is adopted. Each layer includes several neurons, and those in the same layer are not connected to each other. Only unidirectional inter-layer information transmission is supported.

BNodes at each hidden layer represent neurons that provide the computing function.

CInput nodes do not provide the computing function and are used to represent only the element values of an input vector.

DEach neuron is connected to all neurons at the previous layer.

Show Suggested Answer

Suggested Answer: D

This statement is false because not all feedforward neural networks follow this architecture. While fully-connected layers do have this type of connectivity (where each neuron is connected to all neurons in the previous layer), feedforward networks can include layers like convolutional layers, where not every neuron is connected to all previous neurons. Convolutional layers, common in convolutional neural networks (CNNs), only connect to a local region of the input, preserving spatial information.

by Aleta at Sep 15, 2024, 11:50 PM

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Rebeca

2 months ago

Wait, are we talking about actual neural networks or just my morning brain functioning? Because I'm pretty sure all of these options are false when it comes to me before my coffee!

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Shantell

1 months ago

C) Input nodes do not provide the computing function and are used to represent only the element values of an input vector.

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Nakisha

1 months ago

B) Nodes at each hidden layer represent neurons that provide the computing function.

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Bette

2 months ago

A) A unidirectional multi-layer structure is adopted. Each layer includes several neurons, and those in the same layer are not connected to each other. Only unidirectional inter-layer information transmission is supported.

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Tamera

2 months ago

I see your point, but I still think it's A because feedforward neural networks do have connections within the same layer.

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Terrilyn

2 months ago

Hmm, this one's tricky. I'll have to go with option B as the false statement. Nodes at hidden layers don't just represent neurons, they also perform the actual computations.

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Adelina

1 months ago

I think you're right. Option B is the false statement about feedforward neural networks.

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Venita

1 months ago

I see your point, but I still think option B is the incorrect statement. Nodes at hidden layers do more than just represent neurons.

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Rosina

1 months ago

I disagree, I believe option C is the false statement. Input nodes do provide computing functions in a feedforward neural network.

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Vashti

2 months ago

I think option A is false. Each layer in a feedforward neural network is connected to the next layer.

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Chauncey

3 months ago

I disagree, I believe the false statement is C.

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Mozell

3 months ago

Ah, the age-old question of feedforward networks! I'd say option C is the culprit here. Input nodes do provide the computing function, they're not just there to look pretty.

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Huey

2 months ago

C) Input nodes do not provide the computing function and are used to represent only the element values of an input vector.

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Trevor

2 months ago

B) Nodes at each hidden layer represent neurons that provide the computing function.

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Tandra

2 months ago

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Merrilee

3 months ago

Option D is definitely false. Neurons in a feedforward network are not connected to all neurons in the previous layer, that's a characteristic of fully connected networks.

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