Artificial Intelligence Stack Exchange
Artificial Intelligence Stack Exchange

Questions tagged [artificial-neuron]

For questions about what constitutes an artificial neuron and how artificial neurons can be utilized as part of a neural network.

An artificial neuron is a mathematical function inspired by, but does not actually model, biological neurons in mammalian brains. It can be thought of as a function parameterized by a set of weights. These weights are the values that are updated during the update step of a learning algorithm.

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How to find the optimal number of neurons per layer?

When you're writing your algorithm, how do you know how many neurons you need per single layer? Are there any methods for finding the optimal number of them, or is it a rule of thumb?
kenorb
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What does it mean for a neuron in a neural network to be activated?

I just stumbled upon the concept of neuron coverage, which is the ratio of activated neurons and total neurons in a neural network. But what does it mean for a neuron to be "activated"? I know what activation functions are, but what does being…
Leon
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Back-of-the-envelope machine learning (specifically neural networks) calculations

There is a popular story regarding the back-of-the-envelope calculation performed by a British physicist named G. I. Taylor. He used dimensional analysis to estimate the power released by the explosion of a nuclear bomb, simply by analyzing a…
Charles
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How to model inhibitory synapses in the artificial neuron?

In the brain, some synapses are stimulating and some inhibiting. In the case of artificial neural networks, ReLU erases that property, since in the brain inhibition doesn't correspond to a 0 output, but, more precisely, to a negative input. In the…
Ziemo
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Is there research that employs realistic models of neurons?

Is there research that employs realistic models of neurons? Usually, the model of a neuron for a neural network is quite simple as opposed to the realistic neuron, which involves hundreds of proteins and millions of molecules (or even greater…
TomR
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Which artificial neural network can mimic biological neurons the most?

On the Wikipedia page we can read the basic structure of an artificial neuron (a model of biological neurons) which consist: Dendrites - acts as the input vector, Soma - acts as the summation function, Axon - gets its signal from the summation…
kenorb
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How many nodes/hidden layers are required to solve a classification problem where the boundary is a sinusoidal function?

A single neuron is capable of forming a decision boundary between linearly seperable data. Is there any intuition as to how many, and in what configuration, would be necessary to correctly approximate a sinusoidal decision boundary? Thanks
Ian Larson
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Can neurons in MLP and filters in CNN be compared?

I know they are not the same in working, but an input layer sends the input to $n$ neurons with a set of weights, based on these weights and the activation layer, it produces an output that can be fed to the next layer. Aren't the filters the same,…
Tibo Geysen
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Are neurons in layer $l$ only affected by neurons in the previous layer?

Are artificial neurons in layer $l$ only affected by those in layer $l-1$ (providing inputs) or are they also affected by neurons in layer $l$ (and maybe by neurons in other layers)?
George White
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In a neural network, by how much does the number of neurons typically vary from layer to layer?

In a neural network, by how much does the number of neurons typically vary from layer to layer? Note that I am NOT asking how to find the optimal number of neurons per layer. As a hardware design engineer with no practical experience programming…
Angela Johnson
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Do we know what the units of neural networks will do before we train them?

I was learning about back-propagation and, looking at the algorithm, there is no particular 'partiality' given to any unit. What I mean by partiality there is that you have no particular characteristic associated with any unit, and this results in…
Htnamus
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Is the neuron adequately comprehended?

It is possible that the signal handling of a neuron is outside the engineering comprehension of the most astute of human brains, even after the relationships of inputs to outputs are statistically characterized and the mapping of genetic information…
Douglas Daseeco
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What effect does a negative output of a neuron have on neighbouring neurons?

Artificial neural networks are composed of multiple neurons that are connected to each other. When the output of an artificial neuron is zero, it does not have any effect on neighboring neurons. When the output is positive, the neuron has an effect…
Mahdi Amrollahi
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How do biological neurons weights get initialized?

When trying to map artificial neuronal models to biological facts it was not possible to find an answer regarding the biological justification of randomly initializing the weights. Perhaps this is not yet known from our current understanding of…
Leo Gallucci
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How do layers in an artificial neural network transform inputs to outputs?

To me, most ANN/RNN related articles don't tell me actually how the network is implemented. I know that in the ANN you'll have multiple neurons, activation function, weights, etc. But, how do you, actually, in each neuron, convert the input to the…
Andrew.Wolphoe
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