The Bias Neuron

Introduction:-A bias neuron is a neuron whose output value is always 1 and which is represented by It is used to represent neuron biases as connection weights, which enables any weight training algorithm to train the biases at the same time. Then the threshold value of the neurons j₁, j₂. . . j_nis set to 0.The threshold values are implemented as connection weights and can directly be trained together with the connection weights, which considerably facilitates the learning process.

In other words: Instead of including the threshold value in the activation function, it includes the propagation function OrThe threshold value is subtracted from the network input.

Undoubtedly, the advantage of the bias neuron is the fact that it is much easier to implement it in the network. One disadvantage is that the representation of the network already becomes quite ugly with only a few neurons, let alone with a great number of them. By the way, a bias neuronis often referred to as on neuron.