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Apr 16, 2008 · This paper presents a novel non-linear neural activation function architecture that approximates the tanh(nx) function accurately.
Jun 1, 2009 · This paper presents a novel non-linear neural activation function architecture that approximates the tanh(nx) function accurately.
This paper presents a novel non-linear neural activation function architecture that approximates the tanh(nx) function accurately.
Apr 16, 2008 · SUMMARY. This paper presents a novel non-linear neural activation function architecture that approximates the tanh(nx) function accurately.
The key to this work is the constructive use of nonsaturated MOS transistors operating in weak inversion. This provides two improvements. First, circuit ...
This paper presents a novel topology that implements an accurate approximation to the tanh (x) function. This approximation works in current mode and uses ...
This paper presents the hardware implementation of a highly accurate method for tanh computation. Though, the method itself is error free as against the ...
Dec 30, 2020 · Abstract. A CMOS hyperbolic tangent function generator circuit suitable for the implementation of analog neural networks is presented.
ABSTRACT The paper presents in detail a relatively simple implementation method of the hyperbolic tangent function, particularly targeted for FPGAs.
Missing: differential nx)
Feb 25, 2018 · We have 1n−1tanhn−1x=∫tanhn−2xsech2xdx=∫tanhn−2x(1−tanh2x)dx=In−2−In.
Missing: Accurate differential implementation.