In this code, I have explored the sigmoid function, a vital tool in machine learning and neural networks, by visualizing how it behaves with different threshold values. First, the sigmoid function is ...

To develop a python code that creates a simple feed-forward neural networks or perception with the Sigmoid activation function. The neuron has to be trained such that it can predict the correct output ...

This paper studies the influences of variable scales and sigmoid activation functions on the performances of multi-layer perceptrons. Generally speaking, it is not certainly suitable to normalize the ...

The researchers identify that the main challenge with naive sigmoid attention (SigmoidAttn) lies in the large initial attention norms. To address this, they propose several solutions and make ...

This paper investigates the output-tracking control of time-varying linear (TVL) system. Note that the input is always limited in a range due to actuator physical constraints or energy-saving purposes ...