S-curve

The A3IS branch defines [L.sub.ins] as an average cross-entropy loss, which uses the sigmoid function as a neuron activation function.

Table 6 shows the classification accuracy using SDAE-SVM with PReLU and sigmoid functions. SDAE-SVM with PReLU function outperforms SDAE-SVM with sigmoid function on three sample sets.

Lima (14) reported that the sigmoid function was the best in describing the relationship.

The common activation functions are hyperbolic tangent and sigmoid function (table 3).

This neural network has sigmoid function which increased the level of accuracy of the tumor segmentation.

Special functions can be categorized into three, namely, Ramp function, threshold function, and sigmoid function. The popular type among all is the sigmoid function because of its gradient descendent learning algorithm.

A Boltzmann sigmoid function (2) (SigmaPlot 11, Systat Software Inc.) was fitted separately to the right and left SOL, TA, MG, and PL TEPs normalized to the homonymous maximal TEP observed before PAS and plotted against the non-normalized (actual) stimulation intensities for each subject [19, 31].

However, the NHW model contains a sigmoid function for the input and output variables, and [1 1 1 1] and [2 2 8 8] orders for the linear function are utilized to predict the pullout capacity.