A neuron in an artificial neural network performs a "weighted sum" operation followed by an activation function to produce an output.

Here are the steps:

1. Each input is multiplied by a weight: The neuron receives one or more inputs. Each input comes with a weight which can be thought of as the importance of the input. The weight amplifies or attenuates the input.

2. Summation: The results of these multiplications (from step 1) are then added together to produce a single number, which is the weighted sum.

3. Apply an activation function: This weighted sum is then passed through an activation function. The purpose of the activation function is to transform the input signal into an output signal and attach non-linearity to the network. It decides whether a neuron should be activated or not by calculating the weighted sum and further adding bias with it.

4. Output: The result of the activation function is the final output of the neuron. This output can then serve as input to neurons in the next layer of the network.

Question

A neuron in an artificial neural network performs a "weighted sum" operation followed by an activation function to produce an output.

Here are the steps:

1. Each input is multiplied by a weight: The neuron receives one or more inputs. Each input comes with a weight which can be thought of as the importance of the input. The weight amplifies or attenuates the input.

2. Summation: The results of these multiplications (from step 1) are then added together to produce a single number, which is the weighted sum.

3. Apply an activation function: This weighted sum is then passed through an activation function. The purpose of the activation function is to transform the input signal into an output signal and attach non-linearity to the network. It decides whether a neuron should be activated or not by calculating the weighted sum and further adding bias with it.

4. Output: The result of the activation function is the final output of the neuron. This output can then serve as input to neurons in the next layer of the network.

Knowee AI · Accepted Answer

A neuron in an artificial neural network performs a "weighted sum" operation followed by an activation function to produce an output.

Here are the steps:

1. Each input is multiplied by a weight: The neuron receives one or more inputs. Each input comes with a weight which can be thought of as the importance of the input. The weight amplifies or attenuates the input.

2. Summation: The results of these multiplications (from step 1) are then added together to produce a single number, which is the weighted sum.

3. Apply an activation function: This weighted sum is then passed through an activation function. The purpose of the activation function is to transform the input signal into an output signal and attach non-linearity to the network. It decides whether a neuron should be activated or not by calculating the weighted sum and further adding bias with it.

4. Output: The result of the activation function is the final output of the neuron. This output can then serve as input to neurons in the next layer of the network.

A neuron in an artificial neural network performs a ______________ operation followed by an activation function to produce an output.

Question

A neuron in an artificial neural network performs a ______________ operation followed by an activation function to produce an output.

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