Methods of matrix algebra /:
Methods of matrix algebra.
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York :
Academic Press,
1965.
|
| Schriftenreihe: | Mathematics in science and engineering ;
v. 16. |
| Schlagworte: | |
| Online-Zugang: | DE-862 DE-863 DE-862 DE-863 |
| Zusammenfassung: | Methods of matrix algebra. |
| Beschreibung: | 1 online resource (xviii, 406 pages) |
| Format: | Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. |
| Bibliographie: | Includes bibliographical references (pages 396-399) and index. |
| ISBN: | 9780080955223 0080955223 1282289810 9781282289819 |
Internformat
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| 245 | 1 | 0 | |a Methods of matrix algebra / |c Marshall C. Pease, III. |
| 260 | |a New York : |b Academic Press, |c 1965. | ||
| 300 | |a 1 online resource (xviii, 406 pages) | ||
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| 490 | 1 | |a Mathematics in science and engineering ; |v v. 16 | |
| 504 | |a Includes bibliographical references (pages 396-399) and index. | ||
| 588 | 0 | |a Print version record. | |
| 506 | |3 Use copy |f Restrictions unspecified |2 star |5 MiAaHDL | ||
| 533 | |a Electronic reproduction. |b [Place of publication not identified] : |c HathiTrust Digital Library, |d 2010. |5 MiAaHDL | ||
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| 583 | 1 | |a digitized |c 2010 |h HathiTrust Digital Library |l committed to preserve |2 pda |5 MiAaHDL | |
| 520 | |a Methods of matrix algebra. | ||
| 505 | 0 | |a Front Cover; Methods of Matrix Algebra; Copyright Page; Contents; Foreword; Symbols and Conventions; Chapter I. Vectors and Matrices; 1. Vectors; 2. Addition of Vectors and Scalar Multiplication; 3. Linear Vector Spaces; 4. Dimensionality and Bases; 5. Linear Homogeneous Systems-Matrices; 6. Partitioned Matrices; 7. Addition of Matrices and Scalar Multiplication; 8. Multiplication of a Matrix Times a Vector; 9. Matrix Multiplication; 10. An Algebra; 11. Commutativity; 12. Divisors of Zero; 13. A Matrix as a Representation of an Abstract Operator; 14. Other Product Relations | |
| 505 | 8 | |a 15. The Inverse of a Matrix16. Rank of a Matrix; 17. Gauss's Algorithm; 18. 2-Port Networks; 19. Example; Chapter II. The Inner Product; 1. Unitary Inner Product; 2. Alternative Representation of Unitary Inner Product; 3. General (Proper) Inner Product; 4. Euclidean Inner Product; 5. Skew Axes; 6. Orthogonality; 7. Normalization; 8. Gram-Schmidt Process; 9. The Norm of a Vector; Chapter III. Eigenvalues and Eigenvectors; 1. Basic Concept; 2. Characteristic or Iterative Impedance; 3. Formal Development; 4. Determination of the Eigenvalues; 5. Singularity; 6. Linear Independence | |
| 505 | 8 | |a 7. Semisimplicity8. Nonsemisimple Matrices; 9. Degeneracy in a Chain; 10. Examples; 11. p-Section of a Filter; 12. Structure of the Characteristic Equation; 13. Rank of a Matrix; 14. The Trace of a Matrix; 15. Reciprocal Vectors; 16. Reciprocal Eigenvectors; 17. Reciprocal Generalized Eigenvectors; 18. Variational Description of the Eigenvectors and Eigenvalues; Chapter IV. Hermitian, Unitary, and Normal Matrices; 1. Adjoint Relation; 2. Rule of Combination; 3. The Basic Types; 4. Decomposition into Hermitian Components; 5. Polar Decomposition; 6. Structure of Normal Matrices | |
| 505 | 8 | |a 7. The Converse Theorem8. Hermitian Matrices; 9. Unitary Matrices; 10. General (Proper) Inner Product; Chapter V. Change of Basis, Diagonalization, and the Jordan Canonical Form; 1. Change of Basis and Similarity Transformations; 2. Equivalence Transformations; 3. Congruent and Conjunctive Transformations; 4. Example; 5. Gauge Invariance; 6. Invariance of the Eigenvalues under a Change of Basis; 7. Invariance of the Trace; 8. Variation of the Eigenvalues under a Conjunctive Transformation; 9. Diagonalization; 10. Diagonalization of Normal Matrices | |
| 505 | 8 | |a 11. Conjunctive Transformation of a Hermitian Matrix12. Example; 13. Positive Definite Hermitian Forms; 14. Lagrange's Method; 15. Canonical Form of a Nonsemisimple Matrix; 16. Example; 17. Powers and Polynomials of a Matrix; 18. The Cayley-Hamilton Theorem; 19. The Minimum Polynomiail; 20. Examples; 21. Summary; Chapter VI. Functions of a Matrix; 1. Differential Equations; 2. Reduction of Degree; 3. Series Expansion; 4. Transmission Line; 5. Square Root Function; 6. Unitary Matrices as Exponentials; 7. Eigenvectors; 8. Spectrum of a Matrix; 9. Example; 10. Commutativity | |
| 650 | 0 | |a Matrices. |0 http://id.loc.gov/authorities/subjects/sh85082210 | |
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| 650 | 7 | |a Matrices |2 fast | |
| 758 | |i has work: |a Methods of matrix algebra (Work) |1 https://id.oclc.org/worldcat/entity/E39PCFB6qK7xwJQbP3yfT9VKVC |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Pease, Marshall C. (Marshall Carleton), 1920- |t Methods of matrix algebra. |d New York : Academic Press, 1965 |z 9780125488501 |w (DLC) 65019017 |w (OCoLC)528210 |
| 776 | 0 | 8 | |i Online version: |a Pease, Marshall C. (Marshall Carleton), 1920- |t Methods of matrix algebra. |d New York : Academic Press, 1965 |w (OCoLC)1103290370 |
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Datensatz im Suchindex
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| adam_text | |
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| author | Pease, Marshall C. (Marshall Carleton), 1920- |
| author_GND | http://id.loc.gov/authorities/names/n84805212 |
| author_facet | Pease, Marshall C. (Marshall Carleton), 1920- |
| author_role | |
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| author_variant | m c p mc mcp |
| building | Verbundindex |
| bvnumber | localFWS |
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| callnumber-label | QA263 |
| callnumber-raw | QA263 .P36 1965eb |
| callnumber-search | QA263 .P36 1965eb |
| callnumber-sort | QA 3263 P36 41965EB |
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| collection | ZDB-4-EBA |
| contents | Front Cover; Methods of Matrix Algebra; Copyright Page; Contents; Foreword; Symbols and Conventions; Chapter I. Vectors and Matrices; 1. Vectors; 2. Addition of Vectors and Scalar Multiplication; 3. Linear Vector Spaces; 4. Dimensionality and Bases; 5. Linear Homogeneous Systems-Matrices; 6. Partitioned Matrices; 7. Addition of Matrices and Scalar Multiplication; 8. Multiplication of a Matrix Times a Vector; 9. Matrix Multiplication; 10. An Algebra; 11. Commutativity; 12. Divisors of Zero; 13. A Matrix as a Representation of an Abstract Operator; 14. Other Product Relations 15. The Inverse of a Matrix16. Rank of a Matrix; 17. Gauss's Algorithm; 18. 2-Port Networks; 19. Example; Chapter II. The Inner Product; 1. Unitary Inner Product; 2. Alternative Representation of Unitary Inner Product; 3. General (Proper) Inner Product; 4. Euclidean Inner Product; 5. Skew Axes; 6. Orthogonality; 7. Normalization; 8. Gram-Schmidt Process; 9. The Norm of a Vector; Chapter III. Eigenvalues and Eigenvectors; 1. Basic Concept; 2. Characteristic or Iterative Impedance; 3. Formal Development; 4. Determination of the Eigenvalues; 5. Singularity; 6. Linear Independence 7. Semisimplicity8. Nonsemisimple Matrices; 9. Degeneracy in a Chain; 10. Examples; 11. p-Section of a Filter; 12. Structure of the Characteristic Equation; 13. Rank of a Matrix; 14. The Trace of a Matrix; 15. Reciprocal Vectors; 16. Reciprocal Eigenvectors; 17. Reciprocal Generalized Eigenvectors; 18. Variational Description of the Eigenvectors and Eigenvalues; Chapter IV. Hermitian, Unitary, and Normal Matrices; 1. Adjoint Relation; 2. Rule of Combination; 3. The Basic Types; 4. Decomposition into Hermitian Components; 5. Polar Decomposition; 6. Structure of Normal Matrices 7. The Converse Theorem8. Hermitian Matrices; 9. Unitary Matrices; 10. General (Proper) Inner Product; Chapter V. Change of Basis, Diagonalization, and the Jordan Canonical Form; 1. Change of Basis and Similarity Transformations; 2. Equivalence Transformations; 3. Congruent and Conjunctive Transformations; 4. Example; 5. Gauge Invariance; 6. Invariance of the Eigenvalues under a Change of Basis; 7. Invariance of the Trace; 8. Variation of the Eigenvalues under a Conjunctive Transformation; 9. Diagonalization; 10. Diagonalization of Normal Matrices 11. Conjunctive Transformation of a Hermitian Matrix12. Example; 13. Positive Definite Hermitian Forms; 14. Lagrange's Method; 15. Canonical Form of a Nonsemisimple Matrix; 16. Example; 17. Powers and Polynomials of a Matrix; 18. The Cayley-Hamilton Theorem; 19. The Minimum Polynomiail; 20. Examples; 21. Summary; Chapter VI. Functions of a Matrix; 1. Differential Equations; 2. Reduction of Degree; 3. Series Expansion; 4. Transmission Line; 5. Square Root Function; 6. Unitary Matrices as Exponentials; 7. Eigenvectors; 8. Spectrum of a Matrix; 9. Example; 10. Commutativity |
| ctrlnum | (OCoLC)316568667 |
| dewey-full | 512.896 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 512 - Algebra |
| dewey-raw | 512.896 |
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| discipline | Mathematik |
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| id | ZDB-4-EBA-ocn316568667 |
| illustrated | Not Illustrated |
| indexdate | 2025-03-18T14:14:44Z |
| institution | BVB |
| isbn | 9780080955223 0080955223 1282289810 9781282289819 |
| language | English |
| oclc_num | 316568667 |
| open_access_boolean | |
| owner | MAIN DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
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| physical | 1 online resource (xviii, 406 pages) |
| psigel | ZDB-4-EBA FWS_PDA_EBA ZDB-4-EBA |
| publishDate | 1965 |
| publishDateSearch | 1965 |
| publishDateSort | 1965 |
| publisher | Academic Press, |
| record_format | marc |
| series | Mathematics in science and engineering ; |
| series2 | Mathematics in science and engineering ; |
| spelling | Pease, Marshall C. (Marshall Carleton), 1920- https://id.oclc.org/worldcat/entity/E39PCjwqjkJCkjgkPgdPrGxPXq http://id.loc.gov/authorities/names/n84805212 Methods of matrix algebra / Marshall C. Pease, III. New York : Academic Press, 1965. 1 online resource (xviii, 406 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier Mathematics in science and engineering ; v. 16 Includes bibliographical references (pages 396-399) and index. Print version record. Use copy Restrictions unspecified star MiAaHDL Electronic reproduction. [Place of publication not identified] : HathiTrust Digital Library, 2010. MiAaHDL Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. http://purl.oclc.org/DLF/benchrepro0212 MiAaHDL digitized 2010 HathiTrust Digital Library committed to preserve pda MiAaHDL Methods of matrix algebra. Front Cover; Methods of Matrix Algebra; Copyright Page; Contents; Foreword; Symbols and Conventions; Chapter I. Vectors and Matrices; 1. Vectors; 2. Addition of Vectors and Scalar Multiplication; 3. Linear Vector Spaces; 4. Dimensionality and Bases; 5. Linear Homogeneous Systems-Matrices; 6. Partitioned Matrices; 7. Addition of Matrices and Scalar Multiplication; 8. Multiplication of a Matrix Times a Vector; 9. Matrix Multiplication; 10. An Algebra; 11. Commutativity; 12. Divisors of Zero; 13. A Matrix as a Representation of an Abstract Operator; 14. Other Product Relations 15. The Inverse of a Matrix16. Rank of a Matrix; 17. Gauss's Algorithm; 18. 2-Port Networks; 19. Example; Chapter II. The Inner Product; 1. Unitary Inner Product; 2. Alternative Representation of Unitary Inner Product; 3. General (Proper) Inner Product; 4. Euclidean Inner Product; 5. Skew Axes; 6. Orthogonality; 7. Normalization; 8. Gram-Schmidt Process; 9. The Norm of a Vector; Chapter III. Eigenvalues and Eigenvectors; 1. Basic Concept; 2. Characteristic or Iterative Impedance; 3. Formal Development; 4. Determination of the Eigenvalues; 5. Singularity; 6. Linear Independence 7. Semisimplicity8. Nonsemisimple Matrices; 9. Degeneracy in a Chain; 10. Examples; 11. p-Section of a Filter; 12. Structure of the Characteristic Equation; 13. Rank of a Matrix; 14. The Trace of a Matrix; 15. Reciprocal Vectors; 16. Reciprocal Eigenvectors; 17. Reciprocal Generalized Eigenvectors; 18. Variational Description of the Eigenvectors and Eigenvalues; Chapter IV. Hermitian, Unitary, and Normal Matrices; 1. Adjoint Relation; 2. Rule of Combination; 3. The Basic Types; 4. Decomposition into Hermitian Components; 5. Polar Decomposition; 6. Structure of Normal Matrices 7. The Converse Theorem8. Hermitian Matrices; 9. Unitary Matrices; 10. General (Proper) Inner Product; Chapter V. Change of Basis, Diagonalization, and the Jordan Canonical Form; 1. Change of Basis and Similarity Transformations; 2. Equivalence Transformations; 3. Congruent and Conjunctive Transformations; 4. Example; 5. Gauge Invariance; 6. Invariance of the Eigenvalues under a Change of Basis; 7. Invariance of the Trace; 8. Variation of the Eigenvalues under a Conjunctive Transformation; 9. Diagonalization; 10. Diagonalization of Normal Matrices 11. Conjunctive Transformation of a Hermitian Matrix12. Example; 13. Positive Definite Hermitian Forms; 14. Lagrange's Method; 15. Canonical Form of a Nonsemisimple Matrix; 16. Example; 17. Powers and Polynomials of a Matrix; 18. The Cayley-Hamilton Theorem; 19. The Minimum Polynomiail; 20. Examples; 21. Summary; Chapter VI. Functions of a Matrix; 1. Differential Equations; 2. Reduction of Degree; 3. Series Expansion; 4. Transmission Line; 5. Square Root Function; 6. Unitary Matrices as Exponentials; 7. Eigenvectors; 8. Spectrum of a Matrix; 9. Example; 10. Commutativity Matrices. http://id.loc.gov/authorities/subjects/sh85082210 Matrices. MATHEMATICS Algebra Intermediate. bisacsh Matrices fast has work: Methods of matrix algebra (Work) https://id.oclc.org/worldcat/entity/E39PCFB6qK7xwJQbP3yfT9VKVC https://id.oclc.org/worldcat/ontology/hasWork Print version: Pease, Marshall C. (Marshall Carleton), 1920- Methods of matrix algebra. New York : Academic Press, 1965 9780125488501 (DLC) 65019017 (OCoLC)528210 Online version: Pease, Marshall C. (Marshall Carleton), 1920- Methods of matrix algebra. New York : Academic Press, 1965 (OCoLC)1103290370 Mathematics in science and engineering ; v. 16. http://id.loc.gov/authorities/names/n42015986 |
| spellingShingle | Pease, Marshall C. (Marshall Carleton), 1920- Methods of matrix algebra / Mathematics in science and engineering ; Front Cover; Methods of Matrix Algebra; Copyright Page; Contents; Foreword; Symbols and Conventions; Chapter I. Vectors and Matrices; 1. Vectors; 2. Addition of Vectors and Scalar Multiplication; 3. Linear Vector Spaces; 4. Dimensionality and Bases; 5. Linear Homogeneous Systems-Matrices; 6. Partitioned Matrices; 7. Addition of Matrices and Scalar Multiplication; 8. Multiplication of a Matrix Times a Vector; 9. Matrix Multiplication; 10. An Algebra; 11. Commutativity; 12. Divisors of Zero; 13. A Matrix as a Representation of an Abstract Operator; 14. Other Product Relations 15. The Inverse of a Matrix16. Rank of a Matrix; 17. Gauss's Algorithm; 18. 2-Port Networks; 19. Example; Chapter II. The Inner Product; 1. Unitary Inner Product; 2. Alternative Representation of Unitary Inner Product; 3. General (Proper) Inner Product; 4. Euclidean Inner Product; 5. Skew Axes; 6. Orthogonality; 7. Normalization; 8. Gram-Schmidt Process; 9. The Norm of a Vector; Chapter III. Eigenvalues and Eigenvectors; 1. Basic Concept; 2. Characteristic or Iterative Impedance; 3. Formal Development; 4. Determination of the Eigenvalues; 5. Singularity; 6. Linear Independence 7. Semisimplicity8. Nonsemisimple Matrices; 9. Degeneracy in a Chain; 10. Examples; 11. p-Section of a Filter; 12. Structure of the Characteristic Equation; 13. Rank of a Matrix; 14. The Trace of a Matrix; 15. Reciprocal Vectors; 16. Reciprocal Eigenvectors; 17. Reciprocal Generalized Eigenvectors; 18. Variational Description of the Eigenvectors and Eigenvalues; Chapter IV. Hermitian, Unitary, and Normal Matrices; 1. Adjoint Relation; 2. Rule of Combination; 3. The Basic Types; 4. Decomposition into Hermitian Components; 5. Polar Decomposition; 6. Structure of Normal Matrices 7. The Converse Theorem8. Hermitian Matrices; 9. Unitary Matrices; 10. General (Proper) Inner Product; Chapter V. Change of Basis, Diagonalization, and the Jordan Canonical Form; 1. Change of Basis and Similarity Transformations; 2. Equivalence Transformations; 3. Congruent and Conjunctive Transformations; 4. Example; 5. Gauge Invariance; 6. Invariance of the Eigenvalues under a Change of Basis; 7. Invariance of the Trace; 8. Variation of the Eigenvalues under a Conjunctive Transformation; 9. Diagonalization; 10. Diagonalization of Normal Matrices 11. Conjunctive Transformation of a Hermitian Matrix12. Example; 13. Positive Definite Hermitian Forms; 14. Lagrange's Method; 15. Canonical Form of a Nonsemisimple Matrix; 16. Example; 17. Powers and Polynomials of a Matrix; 18. The Cayley-Hamilton Theorem; 19. The Minimum Polynomiail; 20. Examples; 21. Summary; Chapter VI. Functions of a Matrix; 1. Differential Equations; 2. Reduction of Degree; 3. Series Expansion; 4. Transmission Line; 5. Square Root Function; 6. Unitary Matrices as Exponentials; 7. Eigenvectors; 8. Spectrum of a Matrix; 9. Example; 10. Commutativity Matrices. http://id.loc.gov/authorities/subjects/sh85082210 Matrices. MATHEMATICS Algebra Intermediate. bisacsh Matrices fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85082210 |
| title | Methods of matrix algebra / |
| title_auth | Methods of matrix algebra / |
| title_exact_search | Methods of matrix algebra / |
| title_full | Methods of matrix algebra / Marshall C. Pease, III. |
| title_fullStr | Methods of matrix algebra / Marshall C. Pease, III. |
| title_full_unstemmed | Methods of matrix algebra / Marshall C. Pease, III. |
| title_short | Methods of matrix algebra / |
| title_sort | methods of matrix algebra |
| topic | Matrices. http://id.loc.gov/authorities/subjects/sh85082210 Matrices. MATHEMATICS Algebra Intermediate. bisacsh Matrices fast |
| topic_facet | Matrices. MATHEMATICS Algebra Intermediate. Matrices |
| work_keys_str_mv | AT peasemarshallc methodsofmatrixalgebra |