LEADER 04713nam 2200541 a 450 001 9910785790803321 005 20230617012215.0 010 $a1-135-87585-5 010 $a0-203-33723-9 010 $a1-280-10684-0 010 $a1-283-54635-3 010 $a1-135-87586-3 010 $a9786613858801 035 $a(CKB)2670000000238125 035 $a(EBL)199678 035 $a(OCoLC)252951847 035 $a(Au-PeEL)EBL199678 035 $a(CaPaEBR)ebr10094766 035 $a(CaONFJC)MIL10684 035 $a(OCoLC)57587156 035 $a(MiAaPQ)EBC199678 035 $a(EXLCZ)992670000000238125 100 $a20040121d2004 uy 0 101 0 $aeng 135 $aur|n|---||||| 200 00$aReel food$b[electronic resource] $eessays on food and film /$fedited by Anne L. Bower 210 $aNew York $cRoutledge$dc2004 215 $a1 online resource (349 p.) 300 $aDescription based upon print version of record. 311 $a0-415-97110-1 320 $aIncludes bibliographical references and index. 327 $aFront Cover; Reel Food: Essays on Food and Film; Copyright Page; Acknowledgments; Table of Contents; 1. Watching Food: The Production of Food, Film, and Values: Anne L. Bower; Cooking Up Cultural Values; 2. Feel Good Reel Food: A Taste of the Cultural Kedgeree in Gurinder Chadha's: Debnita Chakravarti; 3. Food, Play, Business, and the Image of Japan in Itami Juzo's Tampopo: Michael Ashkenazi; 4. Il Timpano -"To Eat Good Food Is to Be Close to God": The Italian-American Reconciliation of Stanley Tucci and Campbell Scott's Big Night: Margaret Coyle 327 $a5. Cooking Mexicanness: Shaping National Identity in Alfonso Arau's Como agua para chocolate: Miriam Lo?pez-rodri?guez6. Chickens, Cakes, and Kitchens: Food and Modernity in Malay Films of the 1950s and 1960s: Timothy P. Barnard; 7. "I'll Have Whatever She's Having": Jews, Food, and Film: Nathan Abrams; 8. Food as Representative of Ethnicity and Culture in George Tillman Jr.'s Soul Food, Mari?a Ripoll's Tortilla Soup, and Tim Reid's Once upon a Time When We Were Colored: Robin Balthrope; Focus on Gender-The Body, the Spirit 327 $a9. Gendering the Feast: Women, Spirituality, and Grace in Three Food Films: Margaret H. Mcfadden10. Food, Sex, and Power at the Dining Room Table in Zhang Yimou's Raise the Red Lantern: Ellen J. Fried; 11. Anorexia Envisioned: Mike Leigh's Life is Sweet, Chul-Soo Park's 301/302, and Todd Haynes's Superstar: Gretchen Papazian; 12. Production, Reproduction, Food, and Women in Herbert Biberman's Salt of the Earth and Lourdes Portillo and Nina Serrano's After the Earthquake: Carole M. Counihan; 13. Images of Consumption in Jutta Bru?ckner's Years of Hunger: Yogini Joglekar 327 $aMaking Movies, Making Meals14. Appetite for Destruction: Gangster Food and Genre Convention in Quentin Tarantino's Pulp Fiction: Rebecca L. Epstein; 15. "Leave the Gun; Take the Cannoli": Food and Family in the Modern American Mafia Film: Marlisa Santos; 16. All-Consuming Passions: Peter Greenaway's The Cook, the Thief, His Wife and Her Lover: Raymond Armstrong; 17. Jean-Pierre Jeunet and Marc Caro's Delicatessen: An Ambiguous Memory, an Ambivalent Meal: Kyri Watson Claflin; 18. Futuristic Foodways: The Metaphorical Meaning of Food in Science Fiction Film: Laurel Forster 327 $a19. Supper, Slapstick, and Social Class: Dinner as Machine in the Silent Films of Buster Keaton: Eric L. Reinholtz20. Banquet and the Beast: The Civilizing Role of Food in 1930s Horror Films: Blair Davis; 21. Engorged with Desire: The Films of Alfred Hitchcock and the Gendered Politics of Eating: David Greven; 22. What about the Popcorn? Food and the Film-Watching Experience: James Lyons; Notes on Contributors; Index 330 $aReel Food is the first book devoted to food as a vibrant and evocative element of film, featuring original essays by major food studies scholars, among them Carole Counihan and Michael Ashkenazi. This collection reads various films through their uses of food-from major ""food films"" like Babette's Feast and Big Night to less obvious choices including The Godfather trilogy and The Matrix. The contributors draw attention to the various ways in which food is employed to make meaning in film. In some cases, such as Soul Food and Tortilla Soup, for example, food is used to represent racial and eth 606 $aFood in motion pictures 615 0$aFood in motion pictures. 676 $a791.43/6559 701 $aBower$b Anne$01506576 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910785790803321 996 $aReel food$93736869 997 $aUNINA LEADER 12620nam 22006375 450 001 9910299783303321 005 20251113193740.0 010 $a3-319-11080-2 024 7 $a10.1007/978-3-319-11080-6 035 $a(CKB)3710000000306124 035 $a(SSID)ssj0001386586 035 $a(PQKBManifestationID)11716161 035 $a(PQKBTitleCode)TC0001386586 035 $a(PQKBWorkID)11374699 035 $a(PQKB)11257131 035 $a(DE-He213)978-3-319-11080-6 035 $a(MiAaPQ)EBC6312746 035 $a(MiAaPQ)EBC5577943 035 $a(Au-PeEL)EBL5577943 035 $a(OCoLC)989376504 035 $a(PPN)183096088 035 $a(MiAaPQ)EBC1996159 035 $a(EXLCZ)993710000000306124 100 $a20141105d2015 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aLinear Algebra Done Right /$fby Sheldon Axler 205 $a3rd ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource $ccolor illustrations 225 1 $aUndergraduate Texts in Mathematics,$x2197-5604 311 08$a3-319-11079-9 327 $aIntro -- Contents -- Preface for the Instructor -- Preface for the Student -- Acknowledgments -- CHAPTER 1 -- Vector Spaces -- 1.A Rn and Cn -- Complex Numbers -- 1.1 Definition -- 1.2 Example -- 1.3 Properties of complex arithmetic -- 1.4 Example -- 1.5 Definition -- 1.6 Notation -- Lists -- 1.7 Example -- 1.8 Definition -- 1.9 Example -- 1.10 Definition -- 1.11 Example -- 1.12 Definition -- 1.13 Commutativity of addition in Fn -- 1.14 Definition -- 1.15 Example -- 1.16 Definition -- 1.17 Definition -- Digression on Fields -- EXERCISES 1.A -- 1.B Definition of Vector Space -- 1.18 Definition -- 1.19 Definition -- 1.20 Definition -- 1.21 Definition -- 1.22 Example -- 1.23 Notation -- 1.24 Example -- 1.25 Unique additive identity -- 1.26 Unique additive inverse -- 1.27 Notation -- 1.28 Notation -- 1.29 The number 0 times a vector -- 1.30 A number times the vector 0 -- 1.31 The number 1 times a vector -- EXERCISES 1.B -- 1.C Subspaces -- 1.32 Definition -- 1.33 Example -- 1.34 Conditions for a subspace -- 1.35 Example -- Sums of Subspaces -- 1.36 Definition -- 1.37 Example -- 1.38 Example -- 1.39 Sum of subspaces is the smallest containing subspace -- Direct Sums -- 1.40 Definition -- 1.41 Example -- 1.42 Example -- 1.43 Example -- 1.44 Condition for a direct sum -- 1.45 Direct sum of two subspaces -- EXERCISES 1.C -- CHAPTER 2 -- Finite-Dimensional Vector Spaces -- 2.1 Notation -- 2.A Span and Linear Independence -- Linear Combinations and Span -- 2.2 Notation -- 2.3 Definition -- 2.4 Example -- 2.5 Definition -- 2.6 Example -- 2.7 Span is the smallest containing subspace -- 2.8 Definition -- 2.9 Example -- 2.10 Definition -- 2.11 Definition -- 2.12 Definition -- 2.13 Definition -- 2.14 Example -- 2.15 Definition -- 2.16 Example -- Linear Independence -- 2.17 Definition -- 2.18 Example -- 2.20 Example -- 2.21 Linear Dependence Lemma -- 2.22. 327 $a2.23 Length of linearly independent list ? length of spanning list -- 2.24 Example -- 2.25 Example -- 2.26 Finite-dimensional subspaces -- EXERCISES 2.A -- 2.B Bases -- 2.27 Definition -- 2.28 Example -- 2.29 Criterion for basis -- 2.30 -- 2.31 Spanning list contains a basis -- 2.32 Basis of finite-dimensional vector space -- 2.33 Linearly independent list extends to a basis -- 2.34 Every subspace of V is part of a direct sum equal to V -- EXERCISES 2.B -- 2.C Dimension -- 2.35 Basis length does not depend on basis -- 2.36 Definition -- 2.37 Example -- 2.38 Dimension of a subspace -- 2.39 Linearly independent list of the right length is a basis -- 2.40 Example -- 2.41 Example -- 2.42 Spanning list of the right length is a basis -- 2.43 Dimension of a sum -- EXERCISES 2.C -- CHAPTER 3 -- Linear Maps -- 3.1 Notation -- 3.A The Vector Space of Linear Maps -- Definition and Examples of Linear Maps -- 3.2 Definition -- 3.3 Notation -- 3.4 Example -- 3.5 Linear maps and basis of domain -- Algebraic Operations on L(V,W) -- 3.7 L(V,W) is a vector space -- 3.8 Definition -- 3.9 Algebraic properties of products of linear maps -- 3.10 Example -- 3.11 Linear maps take 0 to 0 -- EXERCISES 3.A -- 3.B Null Spaces and Ranges -- Null Space and Injectivity -- 3.12 Definition -- 3.13 Example -- 3.14 The null space is a subspace -- 3.15 Definition -- 3.16 Injectivity is equivalent to null space equals {0} -- Range and Surjectivity -- 3.17 Definition -- 3.18 Example -- 3.19 The range is a subspace -- 3.20 Definition -- 3.21 Example -- Fundamental Theorem of Linear Maps -- 3.22 Fundamental Theorem of Linear Maps -- 3.23 A map to a smaller dimensional space is not injective -- 3.24 A map to a larger dimensional space is not surjective -- 3.25 Example -- 3.26 Homogeneous system of linear equations -- 3.27 Example -- 3.28 -- 3.29 Inhomogeneous system of linear equations. 327 $aEXERCISES 3.B -- 3.C Matrices -- Representing a Linear Map by a Matrix -- 3.30 Definition -- 3.31 Example -- 3.32 Definition -- 3.33 Example -- 3.34 Example -- Addition and Scalar Multiplication of Matrices -- 3.35 Definition -- 3.36 The matrix of the sum of linear maps -- 3.37 Definition -- 3.38 The matrix of a scalar times a linear map -- 3.39 Notation -- 3.40 dim Fm,n = mn -- Matrix Multiplication -- 3.41 Definition -- 3.42 Example -- 3.43 The matrix of the product of linear maps -- 3.44 Notation -- 3.45 Example -- 3.46 Example -- 3.48 Example -- 3.49 Column of matrix product equals matrix times column -- 3.50 Example -- 3.51 Example -- 3.52 Linear combination of columns -- EXERCISES 3.C -- 3.D Invertibility and Isomorphic Vector Spaces -- Invertible Linear Maps -- 3.53 Definition -- 3.54 Inverse is unique -- 3.55 Notation -- 3.56 Invertibility is equivalent to injectivity and surjectivity -- 3.57 Example -- Isomorphic Vector Spaces -- 3.58 Definition -- 3.59 Dimension shows whether vector spaces are isomorphic -- 3.60 L(V -- W) and Fm,n are isomorphic -- 3.61 dimL(V -- W) = (dimV)(dimW) -- Linear Maps Thought of as Matrix Multiplication -- 3.62 Definition -- 3.63 Example -- 3.64 M(T ).,k = M(vk). -- 3.65 Linear maps act like matrix multiplication -- 3.66 -- Operators -- 3.67 Definition -- 3.68 Example -- 3.69 Injectivity is equivalent to surjectivity in finite dimensions -- 3.70 Example -- EXERCISES 3.D -- 3.E Products and Quotients of Vector Spaces -- Products of Vector Spaces -- 3.71 Definition -- 3.72 Example -- 3.73 Product of vector spaces is a vector space -- 3.74 Example -- 3.75 Example -- 3.76 Dimension of a product is the sum of dimensions -- Products and Direct Sums -- 3.77 Products and direct sums -- 3.78 A sum is a direct sum if and only if dimensions add up -- Quotients of Vector Spaces -- 3.79 Definition -- 3.80 Example. 327 $a3.81 Definition -- 3.82 Example -- 3.83 Definition -- 3.84 Example -- 3.85 Two affine subsets parallel to U are equal or disjoint -- 3.86 Definition -- 3.87 Quotient space is a vector space -- 3.88 Definition -- 3.89 Dimension of a quotient space -- 3.90 Definition -- 3.91 Null space and range of T -- EXERCISES 3.E -- 3.F Duality -- The Dual Space and the Dual Map -- 3.92 Definition -- 3.93 Example -- 3.94 Definition -- 3.95 dim V' = dim V -- 3.96 Definition -- 3.97 Example -- 3.98 Dual basis is a basis of the dual space -- 3.99 Definition -- 3.100 Example -- 3.101 Algebraic properties of dual maps -- The Null Space and Range of the Dual of a Linear Map -- 3.102 Definition -- 3.103 Example -- 3.104 Example -- 3.105 The annihilator is a subspace -- 3.106 Dimension of the annihilator -- 3.107 The null space of T' -- 3.108 T' surjective is equivalent to T' injective -- 3.109 The range of T' -- 3.110 T' injective is equivalent to T' surjective -- The Matrix of the Dual of a Linear Map -- 3.111 Definition -- 3.112 Example -- 3.113 The transpose of the product of matrices -- 3.114 The matrix of T' is the transpose of the matrix of T' -- The Rank of a Matrix -- 3.115 Definition -- 3.116 Example -- 3.117 Dimension of range T equals column rank of M(T) -- 3.118 Row rank equals column rank -- 3.119 Definition -- EXERCISES 3.F -- CHAPTER 4 -- Polynomials -- 4.1 Notation -- Complex Conjugate and Absolute Value -- 4.2 Definition -- 4.3 Definition -- 4.4 Example -- 4.5 Properties of complex numbers -- Uniqueness of Coefficients for Polynomials -- 4.6 -- 4.7 If a polynomial is the zero function, then all coefficients are 0 -- The Division Algorithm for Polynomials -- 4.8 Division Algorithm for Polynomials -- Zeros of Polynomials -- 4.9 Definition -- 4.10 Definition -- 4.11 Each zero of a polynomial corresponds to a degree-1 factor. 327 $a4.12 A polynomial has at most as many zeros as its degree -- Factorization of polynomials over C -- 4.13 Fundamental Theorem of Algebra -- 4.14 Factorization of a polynomial over C -- Factorization of polynomials over R -- 4.15 Polynomials with real coefficients have zeros in pairs -- 4.16 Factorization of a quadratic polynomial -- 4.17 Factorization of a polynomial over R -- EXERCISES 4 -- CHAPTER 5 -- Eigenvalues, Eigenvectors, and Invariant Subspaces -- 5.1 Notation -- 5.A Invariant Subspaces -- 5.2 Definition -- 5.3 Example -- 5.4 Example -- Eigenvalues and Eigenvectors -- 5.5 Definition -- 5.6 Equivalent conditions to be an eigenvalue -- 5.7 Definition -- 5.8 Example -- 5.9 -- 5.10 Linearly independent eigenvectors -- 5.11 -- 5.12 -- 5.13 Number of eigenvalues -- Restriction and Quotient Operators -- 5.14 Definition -- 5.15 Example -- EXERCISES 5.A -- 5.B Eigenvectors and Upper-Triangular Matrices -- Polynomials Applied to Operators -- 5.16 Definition -- 5.17 Definition -- 5.18 Example -- 5.19 Definition -- 5.20 Multiplicative properties -- Existence of Eigenvalues -- 5.21 Operators on complex vector spaces have an eigenvalue -- Upper-Triangular Matrices -- 5.22 Definition -- 5.23 Example -- 5.24 Definition -- 5.25 Definition -- 5.26 Conditions for upper-triangular matrix -- 5.27 Over C, every operator has an upper-triangular matrix -- 5.28 -- 5.29 -- 5.30 Determination of invertibility from upper-triangular matrix -- 5.31 -- 5.32 Determination of eigenvalues from upper-triangular matrix -- 5.33 Example -- EXERCISES 5.B -- 5.C Eigenspaces and Diagonal Matrices -- 5.34 Definition -- 5.35 Example -- 5.36 Definition -- 5.37 Example -- 5.38 Sum of eigenspaces is a direct sum -- 5.39 Definition -- 5.40 Example -- 5.41 Conditions equivalent to diagonalizability -- 5.42 -- 5.43 Example -- 5.44 Enough eigenvalues implies diagonalizability. 327 $a5.45 Example. 330 $aThis best-selling textbook for a second course in linear algebra is aimed at undergrad math majors and graduate students. The novel approach taken here banishes determinants to the end of the book. The text focuses on the central goal of linear algebra: understanding the structure of linear operators on finite-dimensional vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. The third edition contains major improvements and revisions throughout the book. More than 300 new exercises have been added since the previous edition. Many new examples have been added to illustrate the key ideas of linear algebra. New topics covered in the book include product spaces, quotient spaces, and dual spaces. Beautiful new formatting creates pages with an unusually pleasant appearance in both print and electronic versions. No prerequisites are assumed other than the usual demand for suitable mathematical maturity. Thus the text starts by discussing vector spaces, linear independence, span, basis, and dimension. The book then deals with linear maps, eigenvalues, and eigenvectors. Inner-product spaces are introduced, leading to the finite-dimensional spectral theorem and its consequences. Generalized eigenvectors are then used to provide insight into the structure of a linear operator. 410 0$aUndergraduate Texts in Mathematics,$x2197-5604 606 $aAlgebras, Linear 606 $aLinear Algebra 615 0$aAlgebras, Linear. 615 14$aLinear Algebra. 676 $a510 700 $aAxler$b Sheldon$4aut$4http://id.loc.gov/vocabulary/relators/aut$059614 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aMonografías 912 $a9910299783303321 996 $aLinear Algebra done right$9374744 997 $aUNINA