LEADER 02174nam0 2200409 i 450 
001 SUN0113725
005 20180125030424.486
010   $d0.00
017 70$2N$a978-3-319-22315-5
100   $a20180118d2015       |0engc50      ba
101   $aeng
102   $aCH
105   $a||||    |||||
200 1 $a*Detection of random signals in dependent gaussian noise$fAntonio F. Gualtierotti
205   $a[Cham] : Springer, 2015
210   $aXXXIV$d1176 p.$cill. ; 24 cm
215   $aPubblicazione in formato elettronico
606   $a60G15$xGaussian processes [MSC 2020]$2MF$3SUNC020010
606   $a60H05$xStochastic integrals [MSC 2020]$2MF$3SUNC020013
606   $a60-XX$xProbability theory and stochastic processes [MSC 2020]$2MF$3SUNC020428
606   $a60H10$xStochastic ordinary differential equations [MSC 2020]$2MF$3SUNC020682
606   $a46E22$xHilbert spaces with reproducing kernels (= [proper] functional Hilbert spaces, including de Branges-Rovnyak and other structured spaces) [MSC 2020]$2MF$3SUNC021306
606   $a60G35$xSignal detection and filtering (aspects of stochastic processes) [MSC 2020]$2MF$3SUNC021485
606   $a60G30$xContinuity and singularity of induced measures [MSC 2020]$2MF$3SUNC026582
606   $a60B11$xProbability theory on linear topological spaces [MSC 2020]$2MF$3SUNC031456
606   $a60G25$xPrediction theory (aspects of stochastic processes) [MSC 2020]$2MF$3SUNC033729
606   $a62M07$xNon-Markovian processes: hypothesis testing [MSC 2020]$2MF$3SUNC033730
606   $a94A13$xDetection theory in information and communication theory [MSC 2020]$2MF$3SUNC033731
620   $aCH$dCham$3SUNL001889
700  1$aGualtierotti$b, Antonio F.$3SUNV087830$0755643
712   $aSpringer$3SUNV000178$4650
801   $aIT$bSOL$c20210503$gRICA
856 4 $uhttp://dx.doi.org/10.1007/978-3-319-22315-5
912   $aSUN0113725
950   $aUFFICIO DI BIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$d08CONS      e-book                  0161        $e08eMF161               20180118            
996   $aDetection of random signals in dependent gaussian noise$91522756
997   $aUNICAMPANIA