Approximation method of softmax function and neural network utilizing the same

A neural network, the neural network having a classifier which has a softmax function computing module, the softmax function computing module converting one or more input values of a k-dimensional vector into one or more output values of a m-dimensional vector, the softmax function computing module including:

• an exponential function approximation computing unit performing a Leaky Rectified Linear Unit (Leaky ReLU) computation on one of the input values of the k-dimensional vector to obtain a Leaky ReLU computation value and performing a polynomial function computation of a certain order based on the Leaky ReLU computation value to obtain an exponential approximation value, wherein the exponential function approximation computing unit further repeatedly processes another one of the input values of the k-dimensional vector to obtain another exponential approximation value;
• an addition computing unit adding the exponential approximation value and the another exponential approximation value to obtain a sum value;
• and
• a division computing unit dividing at least one of the exponential approximation values by the sum value to obtain one of the output values of the m-dimensional vector.