What Are the Best Resources for Understanding Jacobian and Hessian Matrices?

Click For Summary

Discussion Overview

The discussion focuses on identifying resources for understanding Jacobian and Hessian matrices, including their roles as generalizations of derivatives for vector and scalar functions, as well as their connections to concepts like divergence, gradient, and curl. The scope includes recommendations for books and online materials.

Discussion Character

  • Exploratory
  • Technical explanation

Main Points Raised

  • One participant requests recommendations for comprehensive resources on Jacobians and Hessians, emphasizing their mathematical significance.
  • Another participant suggests checking Wikipedia as a potential resource.
  • A different participant mentions finding helpful articles but does not specify which ones.
  • One reply recommends searching for recent works related to E.B. Christoffel, indicating that the topic is complex and may require effort to understand.
  • A participant provides a technical definition of the Hessian matrix, detailing its function and the formula for its elements.

Areas of Agreement / Disagreement

Participants do not appear to reach a consensus on specific resources, and multiple suggestions are offered without agreement on their effectiveness or relevance.

Contextual Notes

Some responses lack specificity regarding the resources mentioned, and there is an acknowledgment of the complexity of the topic, which may influence the search for suitable materials.

YAHA
Messages
121
Reaction score
0
Can someone direct me to a good deep exposition of Jacobians and Hessians? I am especially looking for stuff that pertains to their being generalizations of derivatives of vector and scalar functions as well as div, grad, curl. Book sources or web links are appreciated.
 
Physics news on Phys.org
have you tried looking on wikipedia?
 
Of course. There were a few helpful articles I found.
 
Just go to google.your country and try the words: E.B. Christoffel revisited.

You will find very interesting recent works on that topic.

But ...good luck, because its a hard "stuff"
 
The Hessian is essentially a matrix operator that takes functions [itex]f:\mathbb{R}^{n}\rightarrow\mathbb{R}[/itex] and maps them into [itex]\mathbb{R}^{n\times n}[/itex], the element [itex]H_{ij}[/itex] of the matrix are given by:
[tex] H_{ij}=\frac{\partial^{2}f}{\partial x_{i}\partial x_{j}}[/tex]
 

Similar threads

  • · Replies 1 ·
Replies
1
Views
6K
  • · Replies 5 ·
Replies
5
Views
2K
Replies
8
Views
11K
  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 38 ·
2
Replies
38
Views
12K
  • · Replies 23 ·
Replies
23
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 12 ·
Replies
12
Views
2K
  • · Replies 0 ·
Replies
0
Views
3K