LEADER 02074oam 2200529 450 001 9910713670403321 005 20200622094716.0 035 $a(CKB)5470000002502968 035 $a(OCoLC)966434426 035 $a(OCoLC)995470000002502968 035 $a(EXLCZ)995470000002502968 100 $a20161219d1993 ua 0 101 0 $aeng 135 $aurbn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMethod for predicting water demand for crop uses in New Jersey in 1990, 2000, 2010, and 2020 $eand for estimating water use for livestock and selected sectors of the food-processing industry in New Jersey in 1987 /$fby Rick M. Clawges and Elizabeth O. Titus 210 1$aWest Trenton, New Jersey :$cU.S. Geological Survey,$d1993. 215 $a1 online resource (ix, 211 pages) $cillustrations, maps +$e1 plate 225 1 $aWater-resources investigations report ;$v92-4145 300 $a"Prepared in cooperation with the New Jersey Department of Agriculture." 320 $aIncludes bibliographical references (pages 104-106). 517 $aMethod for predicting water demand for crop uses in New Jersey in 1990, 2000, 2010, and 2020 606 $aWater-supply, Agricultural$zNew Jersey 606 $aWater consumption$zNew Jersey 606 $aWater consumption$2fast 606 $aWater-supply, Agricultural$2fast 607 $aNew Jersey$2fast 615 0$aWater-supply, Agricultural 615 0$aWater consumption 615 7$aWater consumption. 615 7$aWater-supply, Agricultural. 700 $aClawges$b Rick M.$01393224 702 $aTitus$b Elizabeth O. 712 02$aGeological Survey (U.S.), 712 02$aNew Jersey.$bDepartment of Agriculture. 801 0$bCOP 801 1$bCOP 801 2$bOCLCO 801 2$bOCLCF 801 2$bOCLCA 801 2$bGPO 906 $aBOOK 912 $a9910713670403321 996 $aMethod for predicting water demand for crop uses in New Jersey in 1990, 2000, 2010, and 2020$93453539 997 $aUNINA LEADER 01916oam 2200529 450 001 9910713779103321 005 20200724111623.0 035 $a(CKB)5470000002503890 035 $a(OCoLC)966435042 035 $a(OCoLC)995470000002503890 035 $a(EXLCZ)995470000002503890 100 $a20161219d1997 ua 0 101 0 $aeng 135 $aurmn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aStudy of nonpoint source nutrient loading in the Patuxent River Basin, Maryland /$fStephen D. Preston 210 1$aReston, Virginia :$cU.S. Department of the Interior, U.S. Geological Survey,$d1997. 215 $a1 online resource (6 unnumbered pages) $ccolor illustrations, color maps 225 1 $aWater-resources investigations report ;$v96-4273 320 $aIncludes bibliographical references (page 6). 606 $aNutrient pollution of water$zMaryland$zPatuxent River Watershed 606 $aWater quality$zMaryland$zPatuxent River Watershed 606 $aNonpoint source pollution$zMaryland$zPatuxent River Watershed 606 $aNonpoint source pollution$2fast 606 $aNutrient pollution of water$2fast 606 $aWater quality$2fast 607 $aMaryland$zPatuxent River Watershed$2fast 615 0$aNutrient pollution of water 615 0$aWater quality 615 0$aNonpoint source pollution 615 7$aNonpoint source pollution. 615 7$aNutrient pollution of water. 615 7$aWater quality. 700 $aPreston$b Stephen D.$f1955-$01407136 712 02$aGeological Survey (U.S.), 801 0$bCOP 801 1$bCOP 801 2$bOCLCO 801 2$bOCLCF 801 2$bUND 801 2$bGPO 906 $aBOOK 912 $a9910713779103321 996 $aStudy of nonpoint source nutrient loading in the Patuxent River Basin, Maryland$93487729 997 $aUNINA LEADER 05346nam 22007815 450 001 9910483444103321 005 20250609111438.0 010 $a3-319-89620-2 024 7 $a10.1007/978-3-319-89620-5 035 $a(CKB)4100000005471928 035 $a(MiAaPQ)EBC5485432 035 $a(DE-He213)978-3-319-89620-5 035 $a(PPN)229916783 035 $a(MiAaPQ)EBC5917734 035 $a(EXLCZ)994100000005471928 100 $a20180803d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aLow-Rank Approximation $eAlgorithms, Implementation, Applications /$fby Ivan Markovsky 205 $a2nd ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (280 pages) 225 1 $aCommunications and Control Engineering,$x0178-5354 311 08$a3-319-89619-9 327 $aChapter 1. Introduction -- Part I: Linear modeling problems -- Chapter 2. From data to models -- Chapter 3. Exact modelling -- Chapter 4. Approximate modelling -- Part II: Applications and generalizations -- Chapter 5. Applications -- Chapter 6. Data-driven ?ltering and control -- Chapter 7. Nonlinear modeling problems -- Chapter 8. Dealing with prior knowledge -- Index. . 330 $aThis book is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approximation. Local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. A major part of the text is devoted to application of the theory with a range of applications from systems and control theory to psychometrics being described. Special knowledge of the application fields is not required. The second edition of /Low-Rank Approximation/ is a thoroughly edited and extensively rewritten revision. It contains new chapters and sections that introduce the topics of: ? variable projection for structured low-rank approximation; ? missing data estimation; ? data-driven filtering and control; ? stochastic model representation and identification; ? identification of polynomial time-invariant systems; and ? blind identification with deterministic input model. The book is complemented by a software implementation of the methods presented, which makes the theory directly applicable in practice. In particular, all numerical examples in the book are included in demonstration files and can be reproduced by the reader. This gives hands-on experience with the theory and methods detailed. In addition, exercises and MATLAB^® /Octave examples will assist the reader quickly to assimilate the theory on a chapter-by-chapter basis. ?Each chapter is completed with a new section of exercises to which complete solutions are provided.? Low-Rank Approximation (second edition) is a broad survey of the Low-Rank Approximation theory and applications of its field which will be of direct interest to researchers in system identification, control and systems theory, numerical linear algebra and optimization. The supplementary problems and solutions render it suitable for use in teaching graduate courses in those subjects as well. 410 0$aCommunications and Control Engineering,$x0178-5354 606 $aAutomatic control 606 $aRobotics 606 $aMechatronics 606 $aSystem theory 606 $aComputer science?Mathematics 606 $aMathematical models 606 $aArtificial intelligence 606 $aSignal processing 606 $aImage processing 606 $aSpeech processing systems 606 $aControl, Robotics, Mechatronics$3https://scigraph.springernature.com/ontologies/product-market-codes/T19000 606 $aSystems Theory, Control$3https://scigraph.springernature.com/ontologies/product-market-codes/M13070 606 $aSymbolic and Algebraic Manipulation$3https://scigraph.springernature.com/ontologies/product-market-codes/I17052 606 $aMathematical Modeling and Industrial Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/M14068 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aSignal, Image and Speech Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/T24051 615 0$aAutomatic control. 615 0$aRobotics. 615 0$aMechatronics. 615 0$aSystem theory. 615 0$aComputer science?Mathematics. 615 0$aMathematical models. 615 0$aArtificial intelligence. 615 0$aSignal processing. 615 0$aImage processing. 615 0$aSpeech processing systems. 615 14$aControl, Robotics, Mechatronics. 615 24$aSystems Theory, Control. 615 24$aSymbolic and Algebraic Manipulation. 615 24$aMathematical Modeling and Industrial Mathematics. 615 24$aArtificial Intelligence. 615 24$aSignal, Image and Speech Processing. 676 $a511.42 700 $aMarkovsky$b Ivan$4aut$4http://id.loc.gov/vocabulary/relators/aut$0771248 906 $aBOOK 912 $a9910483444103321 996 $aLow rank approximation$91573750 997 $aUNINA