neural_network.activation_functions.soboleva_modified_hyperbolic_tangent
========================================================================

.. py:module:: neural_network.activation_functions.soboleva_modified_hyperbolic_tangent

.. autoapi-nested-parse::

   This script implements the Soboleva Modified Hyperbolic Tangent function.

   The function applies the Soboleva Modified Hyperbolic Tangent function
   to each element of the vector.

   More details about the activation function can be found on:
   https://en.wikipedia.org/wiki/Soboleva_modified_hyperbolic_tangent



Functions
---------

.. autoapisummary::

   neural_network.activation_functions.soboleva_modified_hyperbolic_tangent.soboleva_modified_hyperbolic_tangent


Module Contents
---------------

.. py:function:: soboleva_modified_hyperbolic_tangent(vector: numpy.ndarray, a_value: float, b_value: float, c_value: float, d_value: float) -> numpy.ndarray

   Implements the Soboleva Modified Hyperbolic Tangent function

   Parameters:
       vector (ndarray): A vector that consists of numeric values
       a_value (float): parameter a of the equation
       b_value (float): parameter b of the equation
       c_value (float): parameter c of the equation
       d_value (float): parameter d of the equation

   Returns:
       vector (ndarray): Input array after applying SMHT function

   >>> vector = np.array([5.4, -2.4, 6.3, -5.23, 3.27, 0.56])
   >>> soboleva_modified_hyperbolic_tangent(vector, 0.2, 0.4, 0.6, 0.8)
   array([ 0.11075085, -0.28236685,  0.07861169, -0.1180085 ,  0.22999056,
           0.1566043 ])