This pdf includes the following topics:- Applications of the Gradient Evaluating the Gradient Practice Problems 1 and 2 Meaning of the Gradient Examples
1. Applications of the Gradient • Evaluating the Gradient at a Point • Meaning of the Gradient
2. Evaluating the Gradient In 1-variable calculus, the derivative gives you an equation for the slope at any x-value along f(x). You can then plug in an x-value to find the actual slope at that point. 2 f(x) = x f’(x) = 2x Actual tangent line slope is… 10 when x = 5 -4 when x = -2 5 when x = 2.5 0 when x = 0
3. Evaluating the Gradient Similarly, the gradient gives you an equation for the slope of the tangent plane at any point (x, y) or (x, y, z) or whatever. You can then plug in the actual values at any point to find the slope of the tangent plane at that point. The slope of the tangent plane will be written as a vector, composed of the slopes along each
4. Evaluating the Gradient As an example, given the function f(x, y) = 3x2y – 2x and the point (4, -3), the gradient can be calculated as: [6xy – 2 3x2] Plugging in the values of x and y at (4, -3) gives [-74 48] which is the value of the gradient at that point.
5. Practice Problems 1 and 2 Evaluate the gradient of… 1. f(x, y) = x2 + y2 at a) (0, 0) b) (1, 3) c) (-1, -5) 2. f(x, y, z) = x3z – 2y2x + 5z at a) (1, 1, -4) b) (0, 1, 0) c) (-3, -2, 1)
6. Meaning of the Gradient In the previous example, the function f(x, y) = 3x2y – 2x had a gradient of [6xy – 2 3x2], which at the point (4, -3) came out to [-74 48]. 500 The tangent plane at that 400 300 200 100 (4, -3) point will have a slope of 0 -100 -200 -300 -400 -74 in the x direction and -500 -600 -700 -800 +48 in the y direction. 3 -1 y axis x axis -5 7 Even more important is the vector itself, [-74 48].
7. Meaning of the Gradient Here is the graph again, with the vector drawn in as a vector rather than two sloped lines: Recall that vectors give us 500 400 300 direction as well as magnitude. 200 100 0 -100 -200 The direction of the gradient -300 -400 -500 -600 -700 vector will always point in the 3 -800 -1 direction of steepest increase for y axis x axis -5 7 the function. And, its magnitude will give us the slope of the plane in that direction.
8. Meaning of the Gradient That’s a lot of different slopes! 16 Each component of the gradient 14 vector gives the slope in one 12 10 dimension only. 8 The magnitude of the gradient 6 4 vector gives the steepest possible 2 5 4 slope of the plane. 3 0 2 0 1 1 2 0 3 4 5 6 Recall that the magnitude can be found using the Pythagorean Theorem, c2 = a2 + b2, where c is the magnitude and a and b are the components of the vector.
9. Practice Problem 3 Find the gradient of f(x, y) = 2xy – 2y, and the magnitude of the gradient, at… a) (0, 0) 40 30 b) (5, -3) 20 10 0 -10 -20 c) (20, 10) -30 -40 d) (-5, 4) e) Find where the gradient = 0.
10. Practice Problem 4 Find the gradient of f(x, y, z, w) = 3xy – 2xw + 5xz – 2yw and the magnitude of the gradient at (0, 1, -1, 2).
11. Practice Problem 5 Suppose we are maximizing the function f(x, y) = 4x + 2y – x2 – 3y2 Find the gradient and its magnitude from a) (1, 5) b) (3, -2) c) (2, 0) d) (-4, -6) e) Find where the gradient is 0.
12. Practice Problem 6 Suppose you were trying to minimize f(x, y) = x2 + 2y + 2y2. Along what vector should you travel from (5, 12)?
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