neural_network.activation_functions.squareplus
==============================================

.. py:module:: neural_network.activation_functions.squareplus

.. autoapi-nested-parse::

   Squareplus Activation Function

   Use Case: Squareplus designed to enhance positive values and suppress negative values.
   For more detailed information, you can refer to the following link:
   https://en.wikipedia.org/wiki/Rectifier_(neural_networks)#Squareplus



Functions
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.. autoapisummary::

   neural_network.activation_functions.squareplus.squareplus


Module Contents
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.. py:function:: squareplus(vector: numpy.ndarray, beta: float) -> numpy.ndarray

   Implements the SquarePlus activation function.

   Parameters:
       vector (np.ndarray): The input array for the SquarePlus activation.
       beta (float): size of the curved region

   Returns:
       np.ndarray: The input array after applying the SquarePlus activation.

   Formula: f(x) = ( x + sqrt(x^2 + b) ) / 2

   Examples:
   >>> squareplus(np.array([2.3, 0.6, -2, -3.8]), beta=2)
   array([2.5       , 1.06811457, 0.22474487, 0.12731349])

   >>> squareplus(np.array([-9.2, -0.3, 0.45, -4.56]), beta=3)
   array([0.0808119 , 0.72891979, 1.11977651, 0.15893419])