LEADER 02046nam 2200637 450 001 9910480024203321 005 20170816143245.0 010 $a1-4704-0653-5 035 $a(CKB)3360000000464430 035 $a(EBL)3113561 035 $a(SSID)ssj0000973383 035 $a(PQKBManifestationID)11504617 035 $a(PQKBTitleCode)TC0000973383 035 $a(PQKBWorkID)10959041 035 $a(PQKB)11427038 035 $a(MiAaPQ)EBC3113561 035 $a(PPN)195411293 035 $a(EXLCZ)993360000000464430 100 $a19810515h19811981 uy| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aDecidability and Boolean representations /$fStanley Burris and Ralph McKenzie 210 1$aProvidence, Rhode Island :$cAmerican Mathematical Society,$d[1981] 210 4$dİ1981 215 $a1 online resource (116 p.) 225 1 $aMemoirs of the American Mathematical Society,$x0065-9266 ;$vnumber 246 300 $aDescription based upon print version of record. 311 $a0-8218-2246-2 320 $aIncludes bibliographies. 327 $aDecidable varieties with modular congruence lattices -- Boolean representable varieties. 410 0$aMemoirs of the American Mathematical Society ;$vno. 246. 606 $aAlgebra, Universal 606 $aDecidability (Mathematical logic) 606 $aAlgebraic varieties 606 $aModular lattices 606 $aRepresentations of algebras 608 $aElectronic books. 615 0$aAlgebra, Universal. 615 0$aDecidability (Mathematical logic) 615 0$aAlgebraic varieties. 615 0$aModular lattices. 615 0$aRepresentations of algebras. 676 $a510 s 676 $a512 700 $aBurris$b Stanley$056714 702 $aMcKenzie$b Ralph 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910480024203321 996 $aDecidability and Boolean representations$91952466 997 $aUNINA LEADER 05553nam 2200685 450 001 996426340803316 005 20230120002114.0 010 $a0-12-394784-7 035 $a(CKB)3710000000240366 035 $a(EBL)1789498 035 $a(SSID)ssj0001398889 035 $a(PQKBManifestationID)11810248 035 $a(PQKBTitleCode)TC0001398889 035 $a(PQKBWorkID)11446790 035 $a(PQKB)11760947 035 $a(Au-PeEL)EBL1789498 035 $a(CaPaEBR)ebr10933356 035 $a(CaONFJC)MIL785258 035 $a(OCoLC)891671192 035 $a(CaSebORM)9780123944351 035 $a(MiAaPQ)EBC1789498 035 $a(EXLCZ)993710000000240366 100 $a20140922h20152015 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNumerical linear algebra with applications $eusing matlab /$fby William Ford 205 $aFirst edition. 210 1$aLondon, England :$cAcademic Press,$d2015. 210 4$dİ2015 215 $a1 online resource (629 p.) 300 $aDescription based upon print version of record 311 $a0-12-394435-X 320 $aIncludes bibliographical references and index. 327 $aFront Cover; Numerical Linear Algebra with Applications; Copyright; Dedication; Contents; List of Figures; List of Algorithms; Preface; Matrices; Matrix Arithmetic; Matrix Product; The Trace; MATLAB Examples; Linear Transformations; Rotations; Powers of Matrices; Nonsingular Matrices; The Matrix Transpose and Symmetric Matrices; Chapter Summary; Problems; MATLAB Problems; Linear Equations; Introduction to Linear Equations; Solving Square Linear Systems; Gaussian Elimination; Upper-Triangular Form; Systematic Solution of Linear Systems; Computing the Inverse; Homogeneous Systems 327 $aApplication: A TrussApplication: Electrical Circuit; Chapter Summary; Problems; MATLAB Problems; Subspaces; Introduction; Subspaces of Rn; Linear Independence; Basis of a Subspace; The Rank of a Matrix; Chapter Summary; Problems; MATLAB Problems; Determinants; Developing the Determinant of a 2bold0mu mumu section2 and a 3bold0mu mumu section3 Matrix; Expansion by Minors; Computing a Determinant Using Row Operations; Application: Encryption; Chapter Summary; Problems; MATLAB Problems; Eigenvalues and Eigenvectors; Definitions and Examples; Selected Properties of Eigenvalues and Eigenvectors 327 $aDiagonalizationPowers of Matrices; Applications; Electric Circuit; Irreducible Matrices; Ranking of Teams Using Eigenvectors; Computing Eigenvalues and Eigenvectors using MATLAB; Chapter Summary; Problems; MATLAB Problems; Orthogonal Vectors and Matrices; Introduction; The Inner Product; Orthogonal Matrices; Symmetric Matrices and Orthogonality; The L2 Inner Product; The Cauchy-Schwarz Inequality; Signal Comparison; Chapter Summary; Problems; MATLAB Problems; Vector and Matrix Norms; Vector Norms; Properties of the 2-Norm; Spherical Coordinates; Matrix Norms; The Frobenius Matrix Norm 327 $aInduced Matrix NormsSubmultiplicative Matrix Norms; Computing the Matrix 2-Norm; Properties of the Matrix 2-Norm; Chapter Summary; Problems; MATLAB Problems; Floating Point Arithmetic; Integer Representation; Floating-Point Representation; Mapping from Real Numbers to Floating-Point Numbers; Floating-Point Arithmetic; Relative Error; Rounding Error Bounds; Addition; Multiplication; Matrix Operations; Minimizing Errors; Avoid Adding a Huge Number to a Small Number; Avoid Subtracting Numbers That Are Close; Chapter Summary; Problems; MATLAB Problems; Algorithms; Pseudocode Examples 327 $aInner Product of Two VectorsComputing the Frobenius Norm; Matrix Multiplication; Block Matrices; Algorithm Efficiency; Smaller Flop Count Is Not Always Better; Measuring Truncation Error; The Solution to Upper and Lower Triangular Systems; Efficiency Analysis; The Thomas Algorithm; Efficiency Analysis; Chapter Summary; Problems; MATLAB Problems; Conditioning of Problems and Stability of Algorithms; Why Do We Need Numerical Linear Algebra?; Computation Error; Forward Error; Backward Error; Algorithm Stability; Examples of Unstable Algorithms; Conditioning of a Problem 327 $aPerturbation Analysis for Solving a Linear System 330 $aDesigned for those who want to gain a practical knowledge of modern computational techniques for the numerical solution of linear algebra problems, Numerical Linear Algebra with Applications contains all the material necessary for a first year graduate or advanced undergraduate course on numerical linear algebra with numerous applications to engineering and science. With a unified presentation of computation, basic algorithm analysis, and numerical methods to compute solutions, this book is ideal for solving real-world problems. It provides necessary mathematical background information for 606 $aAlgebras, Linear$xData processing 606 $aEngineering mathematics$xData processing 608 $aProblems and exercises.$2fast 615 0$aAlgebras, Linear$xData processing. 615 0$aEngineering mathematics$xData processing. 676 $a512.5 686 $aST 601$2rvk 686 $aSK 220$2rvk 686 $aST 601 M35$2rvk 700 $aFord$b William H.$01068342 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996426340803316 996 $aNumerical linear algebra with applications$92552992 997 $aUNISA LEADER 01484nas 2200349 n 450 001 990009021660403321 005 20240229084348.0 035 $a000902166 035 $aFED01000902166 035 $a(Aleph)000902166FED01 035 $a000902166 091 $2CNR$aP 00030722 100 $a20161109a19759999km-y0itaa50------ba 101 0 $aeng 110 $aauu-------- 200 1 $aPast and present. 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Plant breeding that once considered ?art and science for changing and improving the characteristics of plants? is now heavily dependent on biotechnologies. The endeavor is a continuous process which results in new varieties required by farmers to improve their crop yields and quality of the produce. On the other hand, in the current scenarios of challenging environmental impact, there is emergence of new insect-pests and new pathotypes of disease causing agents. Accordingly what used to be minor insect-pests/pathogens are rapidly becoming major biotic stress factors. Along with heat and drought, they pose serious threats to crop productivity in many parts of the world. Current WTO analysis reveals that farmers want new high yielding varieties suitable not only for local consumption but also for commercial export. Conventional breeding approaches at this juncture seem inadequate to meet the growing demand for superior varieties. Efficiency improvement of existing cultivars is one way to meet these challenges. Historically, plant improvement has been largely confined to improving yield, quality, resistance to diseases and insect-pests and tolerance to abiotic stresses. Now growers demand high yielding varieties that possess early maturity, higher harvest index, dual purpose forages, varieties with nutrient-use efficiency/water-use efficiency, wider adaptability, suitable for mechanized harvesting, better shelf life, better processing quality, with improved minerals, vitamins, amino acids, proteins, antioxidants and bioactive compounds. Conventional plant breeding methods aiming at the improvement of a self-pollinating crop, such as wheat, usually take 10-12 years to develop and release of the new variety. During the past 10 years, significant advances have been made and accelerated methods have been developed for precision breeding and early release of crop varieties. This multi-volume work summarizes concepts dealing with germplasm enhancement and development of improved varieties based on innovative methodologies that include recent omics approaches, marker assisted selection, marker assisted background selection, genome wide association studies, next generation sequencing, genetic mapping, genomic selection, high-throughput genotyping, high-throughput phenotyping, mutation breeding, reverse breeding, transgenic breeding, speed breeding, genome editing, etc. It is an important reference with special focus on accelerated development of improved forage crop varieties. 410 0$aBiomedical and Life Sciences Series 606 $aPlants$xDevelopment 606 $aPlant physiology 606 $aPlant biotechnology 606 $aAgriculture 606 $aPlant Development 606 $aPlant Physiology 606 $aPlant Biotechnology 606 $aAgriculture 615 0$aPlants$xDevelopment. 615 0$aPlant physiology. 615 0$aPlant biotechnology. 615 0$aAgriculture. 615 14$aPlant Development. 615 24$aPlant Physiology. 615 24$aPlant Biotechnology. 615 24$aAgriculture. 676 $a571.82 700 $aWani$b Shabir Hussain$01854191 701 $aGosal$b S. 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