Tomographic reconstruction from noisy data
A generalized maximum entropy based approach to noisy inverse problems such as the Abel problem, tomography, or deconvolution is discussed and reviewed. Unlike the more traditional regularization approach, in the method discussed here, each unknown parameter (signal and noise) is redefined as a prop...
Saved in:
Published in | Bayesian Inference and and Maximum Entropy Methods in Science and Engineering Vol. 617; pp. 248 - 258 |
---|---|
Main Authors | , |
Format | Conference Proceeding |
Language | English |
Published |
01.01.2002
|
Online Access | Get full text |
ISBN | 0735400636 9780735400634 |
ISSN | 0094-243X |
Cover
Abstract | A generalized maximum entropy based approach to noisy inverse problems such as the Abel problem, tomography, or deconvolution is discussed and reviewed. Unlike the more traditional regularization approach, in the method discussed here, each unknown parameter (signal and noise) is redefined as a proper probability distribution within a certain pre-specified support. Then, the joint entropies of both the noise and signal probabilities are maximized subject to the observed data. We use this method for tomographic reconstruction of the soft X-ray emissivity of hot fusion plasma. |
---|---|
AbstractList | A generalized maximum entropy based approach to noisy inverse problems such as the Abel problem, tomography, or deconvolution is discussed and reviewed. Unlike the more traditional regularization approach, in the method discussed here, each unknown parameter (signal and noise) is redefined as a proper probability distribution within a certain pre-specified support. Then, the joint entropies of both the noise and signal probabilities are maximized subject to the observed data. We use this method for tomographic reconstruction of the soft X-ray emissivity of hot fusion plasma. |
Author | Golan, A Dose, V |
Author_xml | – sequence: 1 givenname: A surname: Golan fullname: Golan, A – sequence: 2 givenname: V surname: Dose fullname: Dose, V |
BookMark | eNotzstKxDAUgOGAIzgdfYeuXAiFk0tzWcrgDQZmM4K7IZdTrbRJTdKFb6-gq3_38TdkE1PEC9KA4r0AkFxuyBbAiI4J_nZFmlI-AZhRSm_J3SnN6T3b5WP0bUafYql59XVMsR1ymtuYxvLdBlvtNbkc7FTw5r878vr4cNo_d4fj08v-_tAtlMraSef4IJXW6GUfmOq9UShR2QCaKeYDZWisHiRzVoGjBqUQ3HgHIXjjDd-R2z93yelrxVLP81g8TpONmNZyZr_jnPac_wA_V0LT |
ContentType | Conference Proceeding |
DBID | 8FD H8D L7M |
DatabaseName | Technology Research Database Aerospace Database Advanced Technologies Database with Aerospace |
DatabaseTitle | Technology Research Database Aerospace Database Advanced Technologies Database with Aerospace |
DatabaseTitleList | Technology Research Database |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Physics Computer Science |
EndPage | 258 |
Genre | Conference Proceeding |
GroupedDBID | -~X 23M 5GY 8FD AAAAW AABDS AAPUP AAYIH ABJGX ACBRY ACZLF ADCTM ADMLS AEJMO AFATG AFHCQ AGKCL AGLKD AGMXG AGTJO AHSDT AJJCW ALEPV ALMA_UNASSIGNED_HOLDINGS ATXIE AWQPM BPZLN F5P FDOHQ FFFMQ H8D HAM J23 L7M M71 M73 NEUPN RIP RQS SJN ~02 |
ID | FETCH-LOGICAL-p116t-6bb3f6788ec65d275c97e6e7ad08272cd12e9a8f62ba70b19e64439cb0ddc9c93 |
ISBN | 0735400636 9780735400634 |
ISSN | 0094-243X |
IngestDate | Fri Jul 11 09:41:05 EDT 2025 |
IsPeerReviewed | true |
IsScholarly | true |
Language | English |
LinkModel | OpenURL |
MergedId | FETCHMERGED-LOGICAL-p116t-6bb3f6788ec65d275c97e6e7ad08272cd12e9a8f62ba70b19e64439cb0ddc9c93 |
Notes | ObjectType-Conference Proceeding-1 SourceType-Conference Papers & Proceedings-1 content type line 25 |
PQID | 27783153 |
PQPubID | 23500 |
PageCount | 11 |
ParticipantIDs | proquest_miscellaneous_27783153 |
PublicationCentury | 2000 |
PublicationDate | 20020101 |
PublicationDateYYYYMMDD | 2002-01-01 |
PublicationDate_xml | – month: 01 year: 2002 text: 20020101 day: 01 |
PublicationDecade | 2000 |
PublicationTitle | Bayesian Inference and and Maximum Entropy Methods in Science and Engineering |
PublicationYear | 2002 |
SSID | ssj0029778 ssj0000367953 |
Score | 1.493893 |
Snippet | A generalized maximum entropy based approach to noisy inverse problems such as the Abel problem, tomography, or deconvolution is discussed and reviewed. Unlike... |
SourceID | proquest |
SourceType | Aggregation Database |
StartPage | 248 |
Title | Tomographic reconstruction from noisy data |
URI | https://www.proquest.com/docview/27783153 |
Volume | 617 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1La-MwEBZtykJPfS67ffrQU4MXW5b1OPaR0pakLTRZcguypEBhYxeSQtNf37Es2QktLO3F-IWR55M1n0f6ZhA6YUSNhYqikHOCQ6K1DCWw8pArQwxjCjhDGRro3dHrAbkdpsOmJqhVl8yyP-rtU13Jd1CFc4BrqZL9ArL1Q-EE7AO-sAWEYfsR409dzbmcGyuDvPHCPZ99td2Tr0-Tl0m7U65Ff563e7ZWtF3-6j_o8raFhIRL3aeYVMmsbYpnVTSJZitFSl48Tedtp2xzGfb_VcHUuk9cuqqNf5dCC3ghtFCl1WJlVAhIDF0cQgUJMbFFfOshlFb6Sz8IVrkznT_FKW98jZ9fv7sfXQ263VG_M-yvojWcMB610NrZZa_7WIfIwLkyO8nn_p-BqlaO1bXARmF8C10yJX9MPvhWSxj6m2i3kVIGDzVyW2jF5Ntow9fSCBwS2-iHXYqrpjvodMH0wbLpg9L0gTV9UJp-Fw2uOv2L69BVtAif45jOQpplyRjoATeKphqzVAlmqGFSAxNjWOkYGyH5mOJMsiiLhQG6mgiVRVoroUTyE7XyIje_UJApLeFzokaNY5LCVc1TrCORcIU1POQ3OvbvP4IRo5wGkrkpXqYjDGZMwNHt_feOfbTedIsD1IK3NYfAwWbZkcPqHWT-NP0 |
linkProvider | EBSCOhost |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=proceeding&rft.title=Bayesian+Inference+and+and+Maximum+Entropy+Methods+in+Science+and+Engineering&rft.atitle=Tomographic+reconstruction+from+noisy+data&rft.au=Golan%2C+A&rft.au=Dose%2C+V&rft.date=2002-01-01&rft.isbn=0735400636&rft.issn=0094-243X&rft.volume=617&rft.spage=248&rft.epage=258&rft.externalDBID=NO_FULL_TEXT |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0094-243X&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0094-243X&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0094-243X&client=summon |