Reference for matrix calculusWhere can I find a broad set of exercises on Matrix calculus?Good introductory...
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Reference for matrix calculus
Where can I find a broad set of exercises on Matrix calculus?Good introductory book for matrix calculusCorrect method to differentiate a first order vector/matrixBook Reference for Calculus and Linear Algebra :: EngineerFormal Variational Calculus Reference RequestReference for Hasse-Witt invariantJoseph Kitchen's Calculus (reference)Reference Request for CalculusInteresting calculus problems for beginnerAdvanced / In-Depth Calculus Book for Self-EdificationReference Book for CalculusSuitable reference for learning symplectic geometryWhich course for deep learning?
$begingroup$
Could someone provide a good reference for learning matrix calculus? I've recently moved to a more engineering-oriented field where it's commonly used and don't have much experience with it.
calculus matrices reference-request
asked Nov 11 '10 at 19:34
SimonSimon
599414
$endgroup$
add a comment |
$begingroup$
Could someone provide a good reference for learning matrix calculus? I've recently moved to a more engineering-oriented field where it's commonly used and don't have much experience with it.
calculus matrices reference-request
asked Nov 11 '10 at 19:34
SimonSimon
599414
$endgroup$
1
$begingroup$
Could you be a bit more specific? What exactly are you trying to learn and what do you already know? Do you want to understand things such as A = exp(Ct) solves dA/dt = CA for A, C matrices? Or perhaps even study matrix Lie groups and their differential properties (I can imagine this could have many engineering applications)?
$endgroup$
– Marek
Nov 11 '10 at 19:46
1
$begingroup$
Well, in linear regression, one can derive a closed-form solution in the form of the normal equations: en.wikipedia.org/wiki/Normal_equations#General_linear_model . The derivation uses results about the gradient of the trace of a matrix product. I guess I just wanted to feel comfortable with these ideas - maybe build up a geometric picture and get some insight as to how everything works.
$endgroup$
– Simon
Nov 11 '10 at 19:55
add a comment |
$begingroup$
Could someone provide a good reference for learning matrix calculus? I've recently moved to a more engineering-oriented field where it's commonly used and don't have much experience with it.
calculus matrices reference-request
asked Nov 11 '10 at 19:34
SimonSimon
599414
$endgroup$
Could someone provide a good reference for learning matrix calculus? I've recently moved to a more engineering-oriented field where it's commonly used and don't have much experience with it.
calculus matrices reference-request
calculus matrices reference-request
asked Nov 11 '10 at 19:34
SimonSimon
599414
asked Nov 11 '10 at 19:34
SimonSimon
599414
asked Nov 11 '10 at 19:34
SimonSimon
599414
asked Nov 11 '10 at 19:34
SimonSimon
599414
asked Nov 11 '10 at 19:34
SimonSimon
599414
599414
1
$begingroup$
Could you be a bit more specific? What exactly are you trying to learn and what do you already know? Do you want to understand things such as A = exp(Ct) solves dA/dt = CA for A, C matrices? Or perhaps even study matrix Lie groups and their differential properties (I can imagine this could have many engineering applications)?
$endgroup$
– Marek
Nov 11 '10 at 19:46
1
$begingroup$
Well, in linear regression, one can derive a closed-form solution in the form of the normal equations: en.wikipedia.org/wiki/Normal_equations#General_linear_model . The derivation uses results about the gradient of the trace of a matrix product. I guess I just wanted to feel comfortable with these ideas - maybe build up a geometric picture and get some insight as to how everything works.
$endgroup$
– Simon
Nov 11 '10 at 19:55
add a comment |
1
$begingroup$
Could you be a bit more specific? What exactly are you trying to learn and what do you already know? Do you want to understand things such as A = exp(Ct) solves dA/dt = CA for A, C matrices? Or perhaps even study matrix Lie groups and their differential properties (I can imagine this could have many engineering applications)?
$endgroup$
– Marek
Nov 11 '10 at 19:46
1
$begingroup$
Well, in linear regression, one can derive a closed-form solution in the form of the normal equations: en.wikipedia.org/wiki/Normal_equations#General_linear_model . The derivation uses results about the gradient of the trace of a matrix product. I guess I just wanted to feel comfortable with these ideas - maybe build up a geometric picture and get some insight as to how everything works.
$endgroup$
– Simon
Nov 11 '10 at 19:55
1
1
$begingroup$
Could you be a bit more specific? What exactly are you trying to learn and what do you already know? Do you want to understand things such as A = exp(Ct) solves dA/dt = CA for A, C matrices? Or perhaps even study matrix Lie groups and their differential properties (I can imagine this could have many engineering applications)?
$endgroup$
– Marek
Nov 11 '10 at 19:46
$begingroup$
Could you be a bit more specific? What exactly are you trying to learn and what do you already know? Do you want to understand things such as A = exp(Ct) solves dA/dt = CA for A, C matrices? Or perhaps even study matrix Lie groups and their differential properties (I can imagine this could have many engineering applications)?
$endgroup$
– Marek
Nov 11 '10 at 19:46
1
1
$begingroup$
Well, in linear regression, one can derive a closed-form solution in the form of the normal equations: en.wikipedia.org/wiki/Normal_equations#General_linear_model . The derivation uses results about the gradient of the trace of a matrix product. I guess I just wanted to feel comfortable with these ideas - maybe build up a geometric picture and get some insight as to how everything works.
$endgroup$
– Simon
Nov 11 '10 at 19:55
$begingroup$
Well, in linear regression, one can derive a closed-form solution in the form of the normal equations: en.wikipedia.org/wiki/Normal_equations#General_linear_model . The derivation uses results about the gradient of the trace of a matrix product. I guess I just wanted to feel comfortable with these ideas - maybe build up a geometric picture and get some insight as to how everything works.
$endgroup$
– Simon
Nov 11 '10 at 19:55
add a comment |
2 Answers
2
active
oldest
votes
$begingroup$
Actually the books cited above by Sivaram are excellent for numerical stuff. If you want "matrix calculus" then the following books might be helpful:
Matrix Differential Calculus with Applications in Statistics and Econometrics by Magnus and Neudecker
Functions of Matrices by N. Higham
Calculus on Manifolds by Spivak
Some classic, but very useful material can also be found in
- Introduction to Matrix Analysis by Bellman.
As a simple example, the books will teach (unless you already know it) how to compute, say, the derivative of $f(X) = logdet(X)$ for an invertible matrix $X$.
$endgroup$
add a comment |
$begingroup$
Gene Howard Golub, Charles F. Van Loan book on "Matrix Computations" is regarded as the "Bhagavad Gita" for Matrix Algorithms.
http://books.google.com/books?id=mlOa7wPX6OYC&printsec=frontcover
There is also another book by "Gene Howard Golub, Gerard Meurant" on "Matrices, moments, and quadrature with applications".
http://books.google.com/books?id=IZvkFET3LlwC&printsec=frontcover
Also, "Numerical Linear Algebra" by Trefethen and Bau is well-written and easy to read.
http://books.google.com/books?id=bj-Lu6zjWbEC&printsec=frontcover
I would highly recommend Trefethen and Bau since I have read it completely. I feel it is ideal for self-study or for a one quarter course. Once you are done with this you can take a look at Golubs' book. Golubs' book is really good for reference.
edited Nov 11 '10 at 19:44
Aryabhata
70.2k6157247
$endgroup$
add a comment |
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2 Answers
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2 Answers
2
active
oldest
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active
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active
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votes
$begingroup$
Actually the books cited above by Sivaram are excellent for numerical stuff. If you want "matrix calculus" then the following books might be helpful:
Matrix Differential Calculus with Applications in Statistics and Econometrics by Magnus and Neudecker
Functions of Matrices by N. Higham
Calculus on Manifolds by Spivak
Some classic, but very useful material can also be found in
- Introduction to Matrix Analysis by Bellman.
As a simple example, the books will teach (unless you already know it) how to compute, say, the derivative of $f(X) = logdet(X)$ for an invertible matrix $X$.
$endgroup$
add a comment |
$begingroup$
Actually the books cited above by Sivaram are excellent for numerical stuff. If you want "matrix calculus" then the following books might be helpful:
Matrix Differential Calculus with Applications in Statistics and Econometrics by Magnus and Neudecker
Functions of Matrices by N. Higham
Calculus on Manifolds by Spivak
Some classic, but very useful material can also be found in
- Introduction to Matrix Analysis by Bellman.
As a simple example, the books will teach (unless you already know it) how to compute, say, the derivative of $f(X) = logdet(X)$ for an invertible matrix $X$.
$endgroup$
add a comment |
$begingroup$
Actually the books cited above by Sivaram are excellent for numerical stuff. If you want "matrix calculus" then the following books might be helpful:
Matrix Differential Calculus with Applications in Statistics and Econometrics by Magnus and Neudecker
Functions of Matrices by N. Higham
Calculus on Manifolds by Spivak
Some classic, but very useful material can also be found in
- Introduction to Matrix Analysis by Bellman.
As a simple example, the books will teach (unless you already know it) how to compute, say, the derivative of $f(X) = logdet(X)$ for an invertible matrix $X$.
$endgroup$
Actually the books cited above by Sivaram are excellent for numerical stuff. If you want "matrix calculus" then the following books might be helpful:
Matrix Differential Calculus with Applications in Statistics and Econometrics by Magnus and Neudecker
Functions of Matrices by N. Higham
Calculus on Manifolds by Spivak
Some classic, but very useful material can also be found in
- Introduction to Matrix Analysis by Bellman.
As a simple example, the books will teach (unless you already know it) how to compute, say, the derivative of $f(X) = logdet(X)$ for an invertible matrix $X$.
answered Nov 12 '10 at 9:53
user1709
add a comment |
add a comment |
$begingroup$
Gene Howard Golub, Charles F. Van Loan book on "Matrix Computations" is regarded as the "Bhagavad Gita" for Matrix Algorithms.
http://books.google.com/books?id=mlOa7wPX6OYC&printsec=frontcover
There is also another book by "Gene Howard Golub, Gerard Meurant" on "Matrices, moments, and quadrature with applications".
http://books.google.com/books?id=IZvkFET3LlwC&printsec=frontcover
Also, "Numerical Linear Algebra" by Trefethen and Bau is well-written and easy to read.
http://books.google.com/books?id=bj-Lu6zjWbEC&printsec=frontcover
I would highly recommend Trefethen and Bau since I have read it completely. I feel it is ideal for self-study or for a one quarter course. Once you are done with this you can take a look at Golubs' book. Golubs' book is really good for reference.
edited Nov 11 '10 at 19:44
Aryabhata
70.2k6157247
$endgroup$
add a comment |
$begingroup$
Gene Howard Golub, Charles F. Van Loan book on "Matrix Computations" is regarded as the "Bhagavad Gita" for Matrix Algorithms.
http://books.google.com/books?id=mlOa7wPX6OYC&printsec=frontcover
There is also another book by "Gene Howard Golub, Gerard Meurant" on "Matrices, moments, and quadrature with applications".
http://books.google.com/books?id=IZvkFET3LlwC&printsec=frontcover
Also, "Numerical Linear Algebra" by Trefethen and Bau is well-written and easy to read.
http://books.google.com/books?id=bj-Lu6zjWbEC&printsec=frontcover
I would highly recommend Trefethen and Bau since I have read it completely. I feel it is ideal for self-study or for a one quarter course. Once you are done with this you can take a look at Golubs' book. Golubs' book is really good for reference.
edited Nov 11 '10 at 19:44
Aryabhata
70.2k6157247
$endgroup$
add a comment |
$begingroup$
Gene Howard Golub, Charles F. Van Loan book on "Matrix Computations" is regarded as the "Bhagavad Gita" for Matrix Algorithms.
http://books.google.com/books?id=mlOa7wPX6OYC&printsec=frontcover
There is also another book by "Gene Howard Golub, Gerard Meurant" on "Matrices, moments, and quadrature with applications".
http://books.google.com/books?id=IZvkFET3LlwC&printsec=frontcover
Also, "Numerical Linear Algebra" by Trefethen and Bau is well-written and easy to read.
http://books.google.com/books?id=bj-Lu6zjWbEC&printsec=frontcover
I would highly recommend Trefethen and Bau since I have read it completely. I feel it is ideal for self-study or for a one quarter course. Once you are done with this you can take a look at Golubs' book. Golubs' book is really good for reference.
edited Nov 11 '10 at 19:44
Aryabhata
70.2k6157247
$endgroup$
Gene Howard Golub, Charles F. Van Loan book on "Matrix Computations" is regarded as the "Bhagavad Gita" for Matrix Algorithms.
http://books.google.com/books?id=mlOa7wPX6OYC&printsec=frontcover
There is also another book by "Gene Howard Golub, Gerard Meurant" on "Matrices, moments, and quadrature with applications".
http://books.google.com/books?id=IZvkFET3LlwC&printsec=frontcover
Also, "Numerical Linear Algebra" by Trefethen and Bau is well-written and easy to read.
http://books.google.com/books?id=bj-Lu6zjWbEC&printsec=frontcover
I would highly recommend Trefethen and Bau since I have read it completely. I feel it is ideal for self-study or for a one quarter course. Once you are done with this you can take a look at Golubs' book. Golubs' book is really good for reference.
edited Nov 11 '10 at 19:44
Aryabhata
70.2k6157247
edited Nov 11 '10 at 19:44
Aryabhata
70.2k6157247
edited Nov 11 '10 at 19:44
Aryabhata
70.2k6157247
edited Nov 11 '10 at 19:44
Aryabhata
70.2k6157247
70.2k6157247
answered Nov 11 '10 at 19:41
user17762
add a comment |
add a comment |
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$begingroup$
Could you be a bit more specific? What exactly are you trying to learn and what do you already know? Do you want to understand things such as A = exp(Ct) solves dA/dt = CA for A, C matrices? Or perhaps even study matrix Lie groups and their differential properties (I can imagine this could have many engineering applications)?
$endgroup$
– Marek
Nov 11 '10 at 19:46
1
$begingroup$
Well, in linear regression, one can derive a closed-form solution in the form of the normal equations: en.wikipedia.org/wiki/Normal_equations#General_linear_model . The derivation uses results about the gradient of the trace of a matrix product. I guess I just wanted to feel comfortable with these ideas - maybe build up a geometric picture and get some insight as to how everything works.
$endgroup$
– Simon
Nov 11 '10 at 19:55