Gradient of functions with multiple variables

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SUMMARY

The gradient of the function f(x,y) = x^2 - x + y is calculated as gradient_f(x,y) = (2x - 1, 1). The analysis reveals that there are no stationary points since the equation 1 = 0 is never satisfied. To find the maximum and minimum values of this function, one must apply the Extreme Value Theorem, which states that extrema occur on the boundary of a bounded domain when stationary points are absent.

PREREQUISITES
  • Understanding of multivariable calculus concepts, specifically gradients.
  • Familiarity with the Extreme Value Theorem in calculus.
  • Knowledge of bounded domains in mathematical analysis.
  • Basic skills in solving equations involving multiple variables.
NEXT STEPS
  • Study the application of the Extreme Value Theorem in multivariable functions.
  • Learn how to analyze boundaries of functions in constrained optimization problems.
  • Explore methods for finding local maxima and minima in functions of several variables.
  • Review the properties and implications of gradients in multivariable calculus.
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Students and professionals in mathematics, particularly those studying calculus and optimization, as well as educators teaching multivariable calculus concepts.

Niles
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Homework Statement


The gradient of f(x,y) = x^2-x+y is:

gradient_f(x,y) = (2x-1 ; 1). To find gradient_f(x,y), I set 2x-1 = 0 and 1 = 0 - so there are no points, where gradient_f(x,y) is zero because of 1 != 0?
 
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And how to I find the maximum and minimum of the function, when there are no stationary points? (gradient_f(x,y) != 0)
 
It's been awhile since I did Calc 3, but if you're in a bounded domain, you can apply the Extreme Value Theorem. Under those circumstances, the max/min likely lie on the boundary.
 

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