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Accurate differential tanh( nx ) implementation
Author(s) -
CarrascoRobles Manuel,
Serrano Luis
Publication year - 2009
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/cta.483
Subject(s) - subthreshold conduction , hyperbolic function , activation function , offset (computer science) , computer science , power consumption , realization (probability) , function (biology) , topology (electrical circuits) , transistor , electronic engineering , algorithm , control theory (sociology) , power (physics) , artificial neural network , mathematics , electrical engineering , engineering , voltage , physics , artificial intelligence , mathematical analysis , statistics , control (management) , quantum mechanics , evolutionary biology , biology , programming language
This paper presents a novel non‐linear neural activation function architecture that approximates the tanh( nx ) function accurately. The purpose of this realization is the description of a circuit that can be designed to obtain different slopes at the origin of the activation function. The special features of transistors working in the subthreshold region are combined with current mode techniques in order to minimize power consumption and occupied area. Moreover, the circuit has been designed with fully differential and balanced topologies so that the external influences, offset, and distortion of even order are reduced. The proposed activation function is thoroughly explained and it is analysed taking the body effect into account. Some modifications are applied in order to immunize it from the body effect, and simulated results for an implementation on a 0.35 µm AMI technology are presented. Copyright © 2008 John Wiley & Sons, Ltd.