Voice Signal Separated Accelerator with Microphone Array
碩士 === 國立中央大學 === 資訊工程學系在職專班 === 102 === The traditional independent component analysis of FastICA faces two of disadvantages, undetermined component of order and offline experiment. We proposed a new solution by using RobustICA algorithem with demixing signal in the frequency domain. RobustICA sepa...
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Others |
Language: | zh-TW |
Published: |
2014
|
Online Access: | http://ndltd.ncl.edu.tw/handle/49680580197375748986 |
id |
ndltd-TW-102NCU05392044 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-TW-102NCU053920442015-10-13T23:55:40Z http://ndltd.ncl.edu.tw/handle/49680580197375748986 Voice Signal Separated Accelerator with Microphone Array 麥克風陣列語音分離硬體加速器設計 Liszt Kao 高亦文 碩士 國立中央大學 資訊工程學系在職專班 102 The traditional independent component analysis of FastICA faces two of disadvantages, undetermined component of order and offline experiment. We proposed a new solution by using RobustICA algorithem with demixing signal in the frequency domain. RobustICA separate independent component by searching demixing vector and using four degree polynomial, supporting complex calculation without whitening progress. The progress which separated component in frequency domain will speed up separated by divided a bunch data into frequency bin with hardware characteristic of parallel process. Moreover, the Non-Gaussianity is obviously in frequency domain. Its shows in experiment that the voice signal separated accelerator have many characteristics including batching progress, ordering component and real time signal separated process. 陳慶瀚 2014 學位論文 ; thesis 70 zh-TW |
collection |
NDLTD |
language |
zh-TW |
format |
Others
|
sources |
NDLTD |
description |
碩士 === 國立中央大學 === 資訊工程學系在職專班 === 102 === The traditional independent component analysis of FastICA faces two of disadvantages, undetermined component of order and offline experiment. We proposed a new solution by using RobustICA algorithem with demixing signal in the frequency domain. RobustICA separate independent component by searching demixing vector and using four degree polynomial, supporting complex calculation without whitening progress. The progress which separated component in frequency domain will speed up separated by divided a bunch data into frequency bin with hardware characteristic of parallel process. Moreover, the Non-Gaussianity is obviously in frequency domain. Its shows in experiment that the voice signal separated accelerator have many characteristics including batching progress, ordering component and real time signal separated process.
|
author2 |
陳慶瀚 |
author_facet |
陳慶瀚 Liszt Kao 高亦文 |
author |
Liszt Kao 高亦文 |
spellingShingle |
Liszt Kao 高亦文 Voice Signal Separated Accelerator with Microphone Array |
author_sort |
Liszt Kao |
title |
Voice Signal Separated Accelerator with Microphone Array |
title_short |
Voice Signal Separated Accelerator with Microphone Array |
title_full |
Voice Signal Separated Accelerator with Microphone Array |
title_fullStr |
Voice Signal Separated Accelerator with Microphone Array |
title_full_unstemmed |
Voice Signal Separated Accelerator with Microphone Array |
title_sort |
voice signal separated accelerator with microphone array |
publishDate |
2014 |
url |
http://ndltd.ncl.edu.tw/handle/49680580197375748986 |
work_keys_str_mv |
AT lisztkao voicesignalseparatedacceleratorwithmicrophonearray AT gāoyìwén voicesignalseparatedacceleratorwithmicrophonearray AT lisztkao màikèfēngzhènlièyǔyīnfēnlíyìngtǐjiāsùqìshèjì AT gāoyìwén màikèfēngzhènlièyǔyīnfēnlíyìngtǐjiāsùqìshèjì |
_version_ |
1718087999508447232 |