Find all local maxima, local minima, and saddle points of each function. Enter each point as an ordered triple, e.g., "(1,5,10)". If there is more than one point of a given type, enter a comma- separated list of ordered triples. If there are no points of a given type, enter "none". f(r, y) = e4v – 2ye5z Local maxima are none Local minima are none Saddle points are none f(r, y) = In(80x + 9y) + 5x² –- 9y Local maxima are none Local minima are none Saddle points are none

Calculus: Early Transcendentals
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ISBN:9781285741550
Author:James Stewart
Publisher:James Stewart
Chapter1: Functions And Models
Section: Chapter Questions
Problem 1RCC: (a) What is a function? What are its domain and range? (b) What is the graph of a function? (c) How...
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### Understanding Local Maxima, Minima, and Saddle Points of a Function

In this lesson, we will find all local maxima, local minima, and saddle points of two given functions. We will enter each point as an ordered triple (e.g., \((1,5,10)\)). If more than one point of a given type exists, we provide a comma-separated list of ordered triples. If there are no points of a given type, we enter "none."

-----

**Function 1:** \( f(x, y) = e^{4y} - 2ye^{5x} \)

- **Local Maxima are:** none
- **Local Minima are:** none
- **Saddle Points are:** none

-----
**Function 2:** \( f(x, y) = \ln(80x + 9y) + 5x^2 - 9y \)

- **Local Maxima are:** none
- **Local Minima are:** none
- **Saddle Points are:** none

-----

### Explanation

#### Local Maxima
Local maxima are points where the function values are higher than those at all nearby points. For both functions \( f(x, y) = e^{4y} - 2ye^{5x} \) and \( f(x, y) = \ln(80x + 9y) + 5x^2 - 9y \), no such points exist. Hence, "none" is listed under local maxima.

#### Local Minima
Local minima are points where the function values are lower than those at all nearby points. Again, for both functions, there are no such points, hence "none" is listed under local minima.

#### Saddle Points
Saddle points are points where the function value is neither a local maximum nor a local minimum but the slope changes direction. For both functions, there are no saddle points, so "none" is listed under saddle points.

-----

Understanding these points is crucial for analyzing the behavior of functions and their graphs. Identifying maxima, minima, and saddle points helps in various applications including optimization problems and understanding the topology of the function graph.
Transcribed Image Text:### Understanding Local Maxima, Minima, and Saddle Points of a Function In this lesson, we will find all local maxima, local minima, and saddle points of two given functions. We will enter each point as an ordered triple (e.g., \((1,5,10)\)). If more than one point of a given type exists, we provide a comma-separated list of ordered triples. If there are no points of a given type, we enter "none." ----- **Function 1:** \( f(x, y) = e^{4y} - 2ye^{5x} \) - **Local Maxima are:** none - **Local Minima are:** none - **Saddle Points are:** none ----- **Function 2:** \( f(x, y) = \ln(80x + 9y) + 5x^2 - 9y \) - **Local Maxima are:** none - **Local Minima are:** none - **Saddle Points are:** none ----- ### Explanation #### Local Maxima Local maxima are points where the function values are higher than those at all nearby points. For both functions \( f(x, y) = e^{4y} - 2ye^{5x} \) and \( f(x, y) = \ln(80x + 9y) + 5x^2 - 9y \), no such points exist. Hence, "none" is listed under local maxima. #### Local Minima Local minima are points where the function values are lower than those at all nearby points. Again, for both functions, there are no such points, hence "none" is listed under local minima. #### Saddle Points Saddle points are points where the function value is neither a local maximum nor a local minimum but the slope changes direction. For both functions, there are no saddle points, so "none" is listed under saddle points. ----- Understanding these points is crucial for analyzing the behavior of functions and their graphs. Identifying maxima, minima, and saddle points helps in various applications including optimization problems and understanding the topology of the function graph.
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