LEADER 00747nam0-22002891i-450- 001 990006621070403321 005 20001010 035 $a000662107 035 $aFED01000662107 035 $a(Aleph)000662107FED01 035 $a000662107 100 $a20001010d--------km-y0itay50------ba 101 0 $aita 105 $ay-------001yy 200 1 $a<>Making of Economics$fE. Ray Canterbery 205 $aII ed. 210 $aBelmont$cWadsworth$d1980 215 $a340 p., 22 cm 700 1$aCanterbery,$bE. Ray$0124936 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990006621070403321 952 $aVI A 258$b20432$fFSPBC 959 $aFSPBC 996 $aMaking of Economics$9615161 997 $aUNINA DB $aGEN01 LEADER 03283nam 2200745 a 450 001 9910824365503321 005 20240506003637.0 010 $a9786612549779 010 $a9781118211212 010 $a1118211219 010 $a9781282549777 010 $a1282549774 010 $a9780470608593 010 $a0470608595 010 $a9780470608586 010 $a0470608587 035 $a(CKB)2670000000011766 035 $a(EBL)487624 035 $a(OCoLC)587390074 035 $a(SSID)ssj0000421539 035 $a(PQKBManifestationID)11277437 035 $a(PQKBTitleCode)TC0000421539 035 $a(PQKBWorkID)10412988 035 $a(PQKB)10573416 035 $a(MiAaPQ)EBC487624 035 $a(Au-PeEL)EBL487624 035 $a(CaPaEBR)ebr10392276 035 $a(CaONFJC)MIL254977 035 $a(OCoLC)368051917 035 $a(FINmELB)ELB178910 035 $a(Perlego)1007221 035 $a(EXLCZ)992670000000011766 100 $a20091102d2010 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aKernel adaptive filtering $ea comprehensive introduction /$fJose C. Principe, Weifeng Liu, Simon Haykin 205 $a1st ed. 210 $aHoboken, N.J. $cWiley$dc2010 215 $a1 online resource (236 p.) 225 1 $aAdaptive and Learning Systems for Signal Processing, Communications and Control Series ;$vv.57 300 $aDescription based upon print version of record. 311 08$a9780470447536 311 08$a0470447532 320 $aIncludes bibliographical references and index. 327 $aKERNEL ADAPTIVE FILTERING; CONTENTS; PREFACE; ACKNOWLEDGMENTS; NOTATION; ABBREVIATIONS AND SYMBOLS; 1 BACKGROUND AND PREVIEW; 2 KERNEL LEAST-MEAN-SQUARE ALGORITHM; 3 KERNEL AFFINE PROJECTION ALGORITHMS; 4 KERNEL RECURSIVE LEAST-SQUARES ALGORITHM; 5 EXTENDED KERNEL RECURSIVE LEAST-SQUARES ALGORITHM; 6 DESIGNING SPARSE KERNEL ADAPTIVE FILTERS; EPILOGUE; APPENDIX; A MATHEMATICAL BACKGROUND; B APPROXIMATE LINEAR DEPENDENCY AND SYSTEM STABILITY; REFERENCES; INDEX 330 $aOnline learning from a signal processing perspective There is increased interest in kernel learning algorithms in neural networks and a growing need for nonlinear adaptive algorithms in advanced signal processing, communications, and controls. Kernel Adaptive Filtering is the first book to present a comprehensive, unifying introduction to online learning algorithms in reproducing kernel Hilbert spaces. Based on research being conducted in the Computational Neuro-Engineering Laboratory at the University of Florida and in the Cognitive Systems Laboratory at McMaster University, 410 0$aAdaptive and Learning Systems for Signal Processing, Communications and Control Series 606 $aAdaptive filters 606 $aKernel functions 615 0$aAdaptive filters. 615 0$aKernel functions. 676 $a621.382/23 700 $aPri?ncipe$b J. C$g(Jose? C.)$01424592 701 $aLiu$b Weifeng$01652184 701 $aHaykin$b Simon S.$f1931-$08857 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910824365503321 996 $aKernel adaptive filtering$94014293 997 $aUNINA