S curve

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Related to Sigmoid function: Gaussian function

S curve

[′es ‚kərv]
(mathematics)
References in periodicals archive ?
Some of the most common types of sigmoid functions are:
Further analysis shows that the DNNA transfer function produces the lowest dissipation of output results (within 1 %) and after the Sigmoid function it can be accepted for the MNN application.
The aforementioned features enable us to use sigmoid function in geometric function theory.
In the particular case of the sigmoid function, this normalization is advantageous for preventing the networks driving the range to the infinity, slowing the learning process.
The shape of pH buffer curves can be approximated by the sigmoid function, Eqn 1:
Cowan (1967) introduces the sigmoid function as activation function.
Using sigmoid function as the activation function and the continuous perceptron as the model of neuron, it is straightforward to arrive at a continuous time Multi-Layer Perceptron.
The logistic sigmoid function, a commonly used activation function has the form of JJ.
Sigmoid function combines nearly linear behaviour, curvilinear behaviour and nearly constant behaviour, depending on the value of the input [15, 16].
The sigmoid function is a bound, monotonic, non-decreasing function that provides graded, non-linear response within a specified range, 0 to 1.
The other findings of this study are that different learning algorithms can increase sensitivity, specificity and accuracy, selecting sigmoid function in ANN structures were also increased the performance.