Multivariable Calculus · 免费预览

方向导数

函数沿任意单位方向的变化率,将其计算为与梯度的点积,以及对梯度长度和方向的解释。

1. The two coordinate directions were only the beginning

The two coordinate directions were only the beginning

2. One dot product does all directions

One dot product does all directions

3. The gradient points the way up

The gradient points the way up

4. Three variables and the same story

Three variables and the same story

5. Computing a directional derivative

For f(x,y)=x2+3y2f(x, y) = x^2 + 3y^2 at (1,1)(1, 1), what is the directional derivative in the direction u=(3/5,4/5)\mathbf{u} = (3/5, 4/5)?

6. The steepest direction

For f(x,y)=x2+3y2f(x, y) = x^2 + 3y^2 at (1,1)(1, 1), in which unit direction does the function increase fastest, and at what rate?

7. Reading the zero directions

At a point where ∇f=(2,6)\nabla f = (2, 6), in which directions is the directional derivative exactly 00?

8. A gradient in three variables

For f(x,y,z)=xyzf(x, y, z) = x y z at the point (1,2,3)(1, 2, 3), give the first component of the gradient, as a plain number.

9. Steepest descent rate

For f(x,y)=x2+3y2f(x, y) = x^2 + 3y^2 at (1,1)(1, 1), give the rate of change along the direction of steepest descent, in the form -a*sqrt(b) with integers.

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