?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=Multi-modal+filtering+for+non-linear+estimation&rft.creator=Kamthe%2C+S&rft.creator=Peters%2C+J&rft.creator=Deisenroth%2C+MP&rft.description=Multi-modal+densities+appear+frequently+in+time+series+and+practical+applications.+However%2C+they+are+not+well+represented+by+common+state+estimators%2C+such+as+the+Extended+Kalman+Filter+and+the+Unscented+Kalman+Filter%2C+which+additionally+suffer+from+the+fact+that+uncertainty+is+often+not+captured+sufficiently+well.+This+can+result+in+incoherent+and+divergent+tracking+performance.+In+this+paper%2C+we+address+these+issues+by+devising+a+non-linear+filtering+algorithm+where+densities+are+represented+by+Gaussian+mixture+models%2C+whose+parameters+are+estimated+in+closed+form.+The+resulting+method+exhibits+a+superior+performance+on+nonlinear+benchmarks.&rft.subject=Science+%26+Technology%2C+Technology%2C+Acoustics%2C+Engineering%2C+Electrical+%26+Electronic%2C+Engineering%2C+State+estimation%2C+Non-linear+dynamical+systems%2C+Non-Gaussian+filtering%2C+Gaussian+sum&rft.publisher=IEEE&rft.date=2014-07-14&rft.type=Proceedings+paper&rft.language=eng&rft.source=+++++In%3A++2014+IEEE+International+Conference+on+Acoustics%2C+Speech+and+Signal+Processing+(ICASSP).++(pp.+pp.+7979-7983).++IEEE%3A+Florence%2C+Italy.+(2014)+++++&rft.format=text&rft.identifier=https%3A%2F%2Fdiscovery.ucl.ac.uk%2Fid%2Feprint%2F10083728%2F1%2F1401.0077v1.pdf&rft.identifier=https%3A%2F%2Fdiscovery.ucl.ac.uk%2Fid%2Feprint%2F10083728%2F&rft.rights=open