Directional and Partial Derivatives ....Notation .... D&K ...

In summary: In order to make the notation more transparent, we can define the directional derivative as follows:##D_j f(a) = \frac{ \partial f }{ \partial x_j } = \frac{ \partial f_1 }{ \partial x_j } (a) + \frac{ \partial f_2 }{ \partial x_j } (a) + \frac{ \partial f_3 }{ \partial x_j } (a)\\and the partial derivative as follows:##D_{ e_j} f(a) = \frac{ \partial f_1 }{ \partial x_j } +
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I am reading "Multidimensional Real Analysis I: Differentiation" by J. J. Duistermaat and J. A. C. Kolk ...

I am focused on Chapter 2: Differentiation ... ...

I need help with an aspect of D&K's notation for directional and partial derivatives ... ...

D&K's definition of directional and partial derivatives reads as follows:
D&K - Start of Section 2.3 on Directional and Partial Derivatives  ... .png


In a previous post I have demonstrated that##D_j f(a) = D_{ e_j} f(a) = D f(a) e_j = \begin{pmatrix} D_j f_1 (a) \\ D_j f_2 (a) \\ D_j f_3 (a) \\ ... \\ ... \\ ... \\ D_j f_p (a) \end{pmatrix}##
I am assuming that in the common 'partials' notation ( Jacobi notation ) that the above can be expressed as follows:
##D_j f(a) = \frac{ \partial f }{ \partial j } = \begin{pmatrix} \frac{ \partial f_1 }{ \partial j } (a) \\ \frac{ \partial f_2 }{ \partial j } (a) \\ \frac{ \partial f_3 }{ \partial j } (a) \\ ... \\ ... \\ ... \\\frac{ \partial f_p }{ \partial j } (a) \end{pmatrix}##Is that correct use of notation/terminology ...?

Peter
 

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In my experience it would be more usual to write ##\frac{\partial f_i}{\partial x_j}## rather than ##\frac{\partial f_i}{\partial j}##. Similarly we would tend to write ##\frac{\partial f}{\partial x_j}## rather than ##\frac{\partial f}{\partial j}##.

Which is a pity, because the way you wrote it is clearer since it does not require implicit assumption of a dummy variable ##x_j##. Just, unfortunately, not common practice.
 
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andrewkirk said:
In my experience it would be more usual to write ##\frac{\partial f_i}{\partial x_j}## rather than ##\frac{\partial f_i}{\partial j}##. Similarly we would tend to write ##\frac{\partial f}{\partial x_j}## rather than ##\frac{\partial f}{\partial j}##.

Which is a pity, because the way you wrote it is clearer since it does not require implicit assumption of a dummy variable ##x_j##. Just, unfortunately, not common practice.
Thanks for pointing that out Andrew ...

I was originally intending to write:

##D_j f(a) = \frac{ \partial f }{ \partial x_j } = \begin{pmatrix} \frac{ \partial f_1 }{ \partial x_j } (a) \\ \frac{ \partial f_2 }{ \partial x_j } (a) \\ \frac{ \partial f_3 }{ \partial x_j } (a) \\ ... \\ ... \\ ... \\\frac{ \partial f_p }{ \partial x_j } (a) \end{pmatrix}##Phew! Learning about ... or further ... getting a good understanding of ... the differentiation of functions/mappings from ##\mathbb{R}^n## to ##\mathbb{R}^p## ... is harder than I thought it would be ... ... :frown:... ...

Peter
 
  • #4
Math Amateur said:
Thanks for pointing that out Andrew ...

I was originally intending to write:

##D_j f(a) = \frac{ \partial f }{ \partial x_j } = \begin{pmatrix} \frac{ \partial f_1 }{ \partial x_j } (a) \\ \frac{ \partial f_2 }{ \partial x_j } (a) \\ \frac{ \partial f_3 }{ \partial x_j } (a) \\ ... \\ ... \\ ... \\\frac{ \partial f_p }{ \partial x_j } (a) \end{pmatrix}##Phew! Learning about ... or further ... getting a good understanding of ... the differentiation of functions/mappings from ##\mathbb{R}^n## to ##\mathbb{R}^p## ... is harder than I thought it would be ... ... :frown:... ...

Peter
Andrew, fresh_42 and other readers

Given your comments on notation I just thought I would share with you both (and with other readers) Duistermaat and Kolk "Remark on notation". This remark is after the definition of directional and partial derivatives and reads as follows:
D&K - 1 -  Remark on notatin  ... ... PART 1 ... .png

D&K - 2 -  Remark on notatin  ... ... PART 2 ... .png
 

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Related to Directional and Partial Derivatives ....Notation .... D&K ...

1. What is the difference between directional and partial derivatives?

Directional derivatives measure the rate of change of a function along a specific direction, while partial derivatives measure the rate of change of a function with respect to one of its variables while holding all other variables constant.

2. What is the notation used for directional and partial derivatives?

The notation for directional derivatives is typically denoted by ∂f/∂u, where u is the direction in which the derivative is taken. For partial derivatives, the notation is similar, but with multiple variables denoted by ∂f/∂x, where x is the variable being held constant.

3. How do directional and partial derivatives relate to the gradient of a function?

The gradient of a function is a vector that points in the direction of the steepest increase of the function. The directional derivative in the direction of the gradient is the maximum rate of change of the function, while the partial derivatives in the direction of each variable are the components of the gradient vector.

4. What is the significance of directional and partial derivatives in real-world applications?

Directional and partial derivatives are important in fields such as physics, engineering, and economics, where they are used to calculate rates of change and optimize functions. They are also used in machine learning and image processing to analyze and manipulate data.

5. How does the D&K notation differ from traditional notation for derivatives?

The D&K notation, also known as Duhamel and Krivine notation, is a more compact and efficient way of writing directional and partial derivatives. It eliminates the need for subscripts and superscripts, making it easier to write and understand equations involving multiple derivatives.

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