[ieee oceans 2007 - vancouver, bc, canada (2007.09.29-2007.10.4)] oceans 2007 - t8 - bayesian signal...

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@Cb1e construction bbhding EM tqi jtrMOt6s~btOdkbLAt l Writing specifications; existiho rtbfbbces f 6tistng pricing and dOliVery Ad'vac ed d et jgite Ethe rhbt f bOroptic Ljhde v-vtbt mdtedbe Otedh82007 exhifbitors ihVb1Vgd ih Lhu=rlwdtbr cablos and connectors will bke ihVitodl to havo f db 1df 6 d11C isc d nd discuss aoo Iir- ti6n hsvvith T8 -- Bayesian Siighd1 Plboossing By Ds Jdf& Cdh* B$E MSE h Chief Sbienh§t fbr EhDirltrenb atd Zfbtrn Df£tSofd df ths Cbh t%r :dt AdVac6d $iDhd & IMOXg Sci'ences dt 1nthcn Mv1 orhWdf Cdfifehl LowsibM&O LivCermr signals from noisy measurements are plagued bV btrors evb1Viho ftrnm t6h8fdiht8 bf the sensors employedz by rdhdr ditturbnces ahd noise dhnd probably I bt mo OtT)mmo n; by thb 1Cdk bf precise knOW1edoe of tho undetlVihd physcal 0hohomenolody genebtiho thd process in the fitt Oldca Methods cdob1e bf xtrdCtfiho the dosittid signal from hostile environments require a1p prFC1C hb that cooturb dll f thke ""d or j,iri inftorma!tlt!io C3Vdildb5e C1hd in)corporaCte fhAerm into a processing schbrho. This apprbdth it tyoiCClly mode1-boa,d! ornoloiho mathematical rbpre-- tentatitins bf the compoerent proesses ihVblVbdl. 1h this thbrt course WO develop the Bdyesian approach to statistical signal orocessing in a tLito- HaCl ftCh ion inclu dih thO -hOx g6h6 ft tjohn

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Page 1: [IEEE Oceans 2007 - Vancouver, BC, Canada (2007.09.29-2007.10.4)] Oceans 2007 - T8 - Bayesian Signal Processing

@Cb1e constructionbbhdingEM tqi jtrMOt6s~btOdkbLAtlWriting specifications; existiho rtbfbbces

f6tistng

pricing and dOliVeryAd'vac ed detjgite Etherhbt fbOroptic Ljhdev-vtbt mdtedbe

Otedh82007 exhifbitors ihVb1Vgd ih Lhu=rlwdtbrcablos and connectors will bke ihVitodl to havofdb1df6 d11Cisc d nd discuss aoo Iir- ti6nhsvvith

T8 -- Bayesian Siighd1 PlboossingBy Ds Jdf& Cdh* B$E MSE h ChiefSbienh§t fbr EhDirltrenb atd Zfbtrn Df£tSofd df thsCbht%r :dtAdVac6d $iDhd & IMOXg Sci'ences dt

1nthcn Mv1orhWdf Cdfifehl LowsibM&O LivCermr

signals from noisy measurements are plaguedbV btrors evb1Viho ftrnm t6h8fdiht8 bf the sensorsemployedz by rdhdr ditturbnces ahd noisedhnd probablyI btmo OtT)mmo n; by thb 1Cdk bfprecise knOW1edoe of tho undetlVihd physcal0hohomenolody genebtiho thd process in thefitt Oldca Methods cdob1e bf xtrdCtfiho thedosittid signal from hostile environments requirea1pprFC1C hb that cooturb dll f thke ""d orj,i riinftorma!tlt!io C3Vdildb5e C1hd in)corporaCte fhAerm intoa processing schbrho. This apprbdth it tyoiCCllymode1-boa,d! ornoloiho mathematical rbpre--tentatitins bf the compoerent proesses ihVblVbdl.1h this thbrt course WO develop the Bdyesianapproach to statistical signal orocessing in a tLito-HaCl ftCh ion includih thO -hOx g6h6 ft tjohn

Page 2: [IEEE Oceans 2007 - Vancouver, BC, Canada (2007.09.29-2007.10.4)] Oceans 2007 - T8 - Bayesian Signal Processing

of proessors thdt have recently, beeh enab1Odwith thb cddVht bf high 81DOOd/high throughoutcompfuters. The cburse commences vvith dhoverview bf Bayesian iffet6hpo frm bdt(Dhtb sb(qdahtidl processors Ohtb the evolvingBdybtian patdiorn is bstdblithed~simulation-based rnethods LAsing sampling theory dhd MbhfbCarlo todlitcifions are disbussod. Hbtb thb usuallirnitdtibhs bf hbhlihear approximafions and hbn-Gaussian processes ptOvd1brit ir) ClCidsil nonlinearprocessing d1dbrithrn (bd.g Kdlrnd f1tfor) ore no

lbobte d restriction tbOpetfbrn Bcg@iyein hfbrbhce.Nod: imp6ttance sdrnoliho methods orb discussedddtbhh tecabe xhddt 8eie-tidl 8610tibrit. With this in mindg thb concept bf Cparticle filteg: d discrete hbnpararnbtic reprsen-tdtibh bf d prDbbblifiiy dlistribtution, it developeddhd shbWh how it can bb implemented usingsequehfiCidilrobrtnce sOmpliho/ksSOmplingrnbfhbd8 f p tern stdfisticaII f1tbh es yib uIdd 8Uito bf pobold estimators such at tho doholi-tibhdl bXOctdfib; maximum 01-pCotefi6ri ndhrnbdicih filtors. FlhdllyW d set bf applications aredicusse compain the performace f thodtiifII FltoF dbt1gh witW TJclassical1 irnrDlbrnbhft--tiohs (Kd1rna fltots). Participants Will bo ihttn=dLAtbd1 tb d Variety bf statisticl signal processingtechJniques coupled1 With dIIDilatibht tb demon-stntdt thA@it tdpdbilifyC6urtO OUtline:

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Infermenc4. SOod6hidnil BCiyesian processot (SBP)5. Modioi-loisod signail processing: (Kaltman flltb(6. Bdyeiaeln aipproacih tb 8tteit0apcie processors

Page 3: [IEEE Oceans 2007 - Vancouver, BC, Canada (2007.09.29-2007.10.4)] Oceans 2007 - T8 - Bayesian Signal Processing

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arrayt carriet4lohd8b dhd 8yMbbI t1 irnih recovery;1Dpolo1r tomnpensdtibh ndho multi-usor dletbttionrhethbdbjb&i8S The tutbitidl is 8ditCbibi ftF modemengineerswith limited orno experienc(D ir)this areatb aIs1sit thbr- ih thb design bf UA based CObmmu nl-c,dtibh 8syt1ms.