LEADER 00574nam 2200169z- 450 001 9910690355803321 035 $a(CKB)5470000002337734 035 $a(EXLCZ)995470000002337734 100 $a20230503c1996uuuu -u- - 101 0 $aeng 200 10$aExecutive summary : visitors survey 210 $cOffice of Ocean Resources Conservation and Assessment, National Ocean Service, National Oceanic and Atmospheric Administration 517 $aExecutive summary 906 $aBOOK 912 $a9910690355803321 996 $aExecutive summary : visitors survey$93178434 997 $aUNINA LEADER 04085nam 22006255 450 001 9911049076703321 005 20260102120637.0 010 $a3-032-06740-5 024 7 $a10.1007/978-3-032-06740-1 035 $a(CKB)44770159700041 035 $a(MiAaPQ)EBC32470319 035 $a(Au-PeEL)EBL32470319 035 $a(DE-He213)978-3-032-06740-1 035 $a(EXLCZ)9944770159700041 100 $a20260102d2026 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvanced Digital Signal Processing Methods for Filtering, Identification, and Nonlinear Systems Control /$fby Rimantas Pupeikis, Kazys Kazlauskas 205 $a1st ed. 2026. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2026. 215 $a1 online resource (249 pages) 225 1 $aStudies in Systems, Decision and Control,$x2198-4190 ;$v638 311 08$a3-032-06739-1 327 $a1. Introdution -- 2. High Speed Least Mean Square Adaptive Filtering -- 3. Optimal Parametri Identi ation of Linear Periodially Time-variant Systems -- 4. Iterative Parametric Identiation Algorithm of Autoregression -- 5. Layered Polynomial Filter Strutures -- 6. Exploring the Potentiality of Nonlinear Systems for Minimum Variane Control -- 7. Parametri Identiation of Systems with Pieewise-linear Nonlinearities -- 8. Parametri Identiation of Systems with Deadzones -- 9. Controlled Wiener System Simulation -- A Consistent parametri identiation -- Examples of the use of DSP methods for modelling, ltering, identiation, and control. 330 $aThis book presents a general approach to block and recursive filtering, identification, and control, using signal observations processing techniques, and among others provides to the reader these results: The new version of least square algorithm that is speeded up without changing its adaptive characteristics, increasing the parallelism in algorithm. The efficient lower triangular inverse matrix and the input signal covariance matrix computation method. The original bias correction approach that is used to eliminate the parameter estimation bias of an iterative autoregressive system parameter estimation algorithm in the presence of additive white noise. The discovery that nonlinear Volterra, polynomial autoregressive and bilinear systems have the same layered implementation routine, which allows us using the layered structure, the order of nonlinearity increased/decreased by adding/deleting more layers to/from the structure. The proven statement that the modular layered structures admit the very large scale integration implementation of the polynomial nonlinear filters. The book is aimed at three major groups of readers: senior undergraduate students, graduate students, and scientific research workers in electrical engineering, computer engineering, computer science, and digital control. 410 0$aStudies in Systems, Decision and Control,$x2198-4190 ;$v638 606 $aDynamics 606 $aNonlinear theories 606 $aAutomatic control 606 $aEngineering mathematics 606 $aEngineering$xData processing 606 $aApplied Dynamical Systems 606 $aControl and Systems Theory 606 $aMathematical and Computational Engineering Applications 615 0$aDynamics. 615 0$aNonlinear theories. 615 0$aAutomatic control. 615 0$aEngineering mathematics. 615 0$aEngineering$xData processing. 615 14$aApplied Dynamical Systems. 615 24$aControl and Systems Theory. 615 24$aMathematical and Computational Engineering Applications. 676 $a515.39 700 $aPupeikis$b Rimantas$01887133 701 $aKazlauskas$b Kazys$01887134 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911049076703321 996 $aAdvanced Digital Signal Processing Methods for Filtering, Identification, and Nonlinear Systems Control$94523040 997 $aUNINA