Respuesta :
Answer:
[tex]\displaystyle \nabla f(\sqrt{2}, 1) = 2\sqrt{2} \hat{\i} - 2 \hat{\j}[/tex]
General Formulas and Concepts:
Calculus
Differentiation
- Derivatives
- Derivative Notation
Derivative Rule [Basic Power Rule]:
- f(x) = cxⁿ
- f’(x) = c·nxⁿ⁻¹
Multivariable Calculus
Differentiation
- Partial Derivatives
- Derivative Notation
Gradient: [tex]\displaystyle \nabla f(x, y, z) = \frac{\partial f}{\partial x} \hat{\i} + \frac{\partial f}{\partial y} \hat{\j} + \frac{\partial f}{\partial z} \hat{\text{k}}[/tex]
Gradient Property [Addition/Subtraction]: [tex]\displaystyle \nabla \big[ f(x) + g(x) \big] = \nabla f(x) + \nabla g(x)[/tex]
Step-by-step explanation:
Step 1: Define
Identify.
[tex]\displaystyle f(x, y) = x^2 - y^2[/tex]
[tex]\displaystyle P(\sqrt{2}, 1)[/tex]
Step 2: Find Gradient
- [Function] Differentiate [Gradient]: [tex]\displaystyle \nabla f(x, y) = \frac{\partial f}{\partial x} \bigg[ x^2 - y^2 \bigg] \hat{\i} + \frac{\partial f}{\partial y} \bigg[ x^2 - y^2 \bigg] \hat{\j}[/tex]
- [Gradient] Rewrite [Gradient Property - Addition/Subtraction]: [tex]\displaystyle \nabla f(x, y) = \bigg[ \frac{\partial f}{\partial x}(x^2) - \frac{\partial f}{\partial x}(y^2) \bigg] \hat{\i} + \bigg[ \frac{\partial f}{\partial y}(x^2) - \frac{\partial f}{\partial y}(y^2) \bigg] \hat{\j}[/tex]
- [Gradient] Differentiate [Derivative Rule - Basic Power Rule]: [tex]\displaystyle \nabla f(x, y) = 2x \hat{\i} - 2y \hat{\j}[/tex]
- [Gradient] Substitute in point: [tex]\displaystyle \nabla f(\sqrt{2}, 1) = 2\sqrt{2} \hat{\i} - 2(1) \hat{\j}[/tex]
- [Gradient] Simplify: [tex]\displaystyle \nabla f(\sqrt{2}, 1) = 2\sqrt{2} \hat{\i} - 2 \hat{\j}[/tex]
∴ the gradient of the given f(x, y) function is equal to <2√2, -2>.
---
Learn more about gradient: https://brainly.com/question/15306869
Learn more about multivariable calculus: https://brainly.com/question/17433118
---
Topic: Multivariable Calculus
Unit: Directional Derivatives
![Ver imagen Space](https://us-static.z-dn.net/files/deb/c3ded94490a40b595d6598f7bfc777c2.jpg)