contributor author | Fuliang Wang | |
contributor author | Junhui Li | |
contributor author | Shaohua Liu | |
contributor author | Lei Han | |
date accessioned | 2020-03-12T23:51:25Z | |
date available | 2020-03-12T23:51:25Z | |
date issued | 2014 | |
identifier issn | 0894-6507 | |
identifier other | 6762998.pdf | |
identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/1125806?locale-attribute=fa&show=full | |
format | general | |
language | English | |
publisher | IEEE | |
title | Heavy Aluminum Wire Wedge Bonding Strength Prediction Using a Transducer Driven Current Signal and an Artificial Neural Network | |
type | Journal Paper | |
contenttype | Metadata Only | |
identifier padid | 8305514 | |
subject keywords | aluminium alloys | |
subject keywords | backpropagation | |
subject keywords | electronic engineering computing | |
subject keywords | electronics packaging | |
subject keywords | lead bonding | |
subject keywords | mechanical strength | |
subject keywords | neural nets | |
subject keywords | transducers | |
subject keywords | wavelet transforms | |
subject keywords | Al | |
subject keywords | artificial neural network training | |
subject keywords | backpropagation | |
subject keywords | bonding test samples | |
subject keywords | data acquisition system | |
subject keywords | fundamental frequency component | |
subject keywords | heavy aluminum wire wedge bonding strength prediction system | |
subject keywords | power electronic devices | |
subject keywords | shear strength | |
subject keywords | transducer driven current signal | |
subject keywords | wavelet model | |
subject keywords | Acoustics | |
subject keywords | Aluminum | |
subject keywords | Artificial neura | |
identifier doi | 10.1109/TSM.2014.2310223 | |
journal title | Semiconductor Manufacturing, IEEE Transactions on | |
journal volume | 27 | |
journal issue | 2 | |
filesize | 11797031 | |
citations | 0 | |