MindMap Gallery Chapter 8 Differential Calculus of Multivariate Functions
Wu Zhongxiang’s course study notes, refer to the teacher’s course notes; very useful during final review ~ suitable for exam review!
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Differential calculus of multivariate functions
Extreme values and maximum values of multivariate functions
Unconstrained extreme value
definition
The point function value is the maximum/minimum value of all function values in the neighborhood of the point
Necessary conditions for extreme values
premise
1. f(x,y) has a partial derivative at point (x0,y0)
2. Point (x0, y0) is the extreme point of f (x, y)
in conclusion
The function value of the two first-order partial derivatives at this point is 0
Sufficient conditions for extreme values
premise
1. The function value of the two first-order partial derivatives at this point is 0 (a necessary condition for extreme values)
2. f(x,y) has a second-order continuous partial derivative in a certain neighborhood of point (x0,y0)
Conclusion P88
Possible extreme points
1. stationary point
2. The first-order partial derivative has at least one non-existent point (an undifferentiable point of a function of one variable)
Conditional extreme values (constrained extreme values) and Lagrangian number multiplication
Maximum and minimum values
Find the maximum and minimum values of the continuous function f(x,y) on the bounded closed area D
Find the possible extreme points of f(x,y) inside region D
Find the maximum and minimum points of f(x,y) on the boundary of area D (conditional extreme value)
Lagrangian multiplication
Turn conditional into unconditional
y=y(x)
z(x,y)--->z(x,f(x)) (about the extreme value of the one-variable function of x)
parametric equation method
Boundary curve is circle/ellipse
Application questions
Establish the objective function z=f(x,y)
Follow the above steps to find the maximum value of f(x,y) on the bounded closed area D
Basic concepts of multivariate functions
Limits of multivariate functions
definition
It is required that point (x, y) approaches point (x0, y0) in any way within D, and f (x, y) approaches the same certain constant A.
Calculate (x->0,y->0)
1. Ratio of the numerator to the power of the denominator (preliminary judgment)
High - the limit generally exists
Low or equal - limits generally do not exist
2. Taking the absolute value and forcing it - easy to scale (generalization of the limit conclusion of the sequence)
Prove that the limit does not exist
1. Take the special path y=kx
2. Find the original weight limit
The limit value is related to k (heavy limit does not exist)
Notice
If f(x,y) approaches the point (x0,y0) along any two directions in D, the limit does not exist if the function values are not the same.
Multivariable functions without Lupida
Continuity of multivariate functions
Test points
Just be able to judge whether a multivariate function is continuous or not
definition
The limit value of the function at this point = function value
Properties (corresponding to one-variable functions)
The sum, difference and product quotient of a multivariate continuous function (the denominator is not 0) is still a continuous function
The composite function of a multivariate continuous function is still a continuous function
A multivariate elementary function is continuous within its defined region (unary - defined interval)
maximum value theorem
Intermediate value theorem
Notice
Multivariate functions do not discuss discontinuity types (complex)
Partial derivative
definition
definition
The limit of (partial increment of function/increment of independent variable) (increment of independent variable -->0)
Calculation method
First seek (define) descendants
Find first (specific point) and then find
Notice
Partial derivatives are essentially derivatives of functions of one variable
Geometric meaning
The tangent of the angle between the tangent direction and the direction vector in the ∥ coordinate axis direction
Higher order partial derivatives
The n-order mixed partial derivatives are continuous in region D --->The n-order mixed partial derivatives are equal in region D
Contain abstract functions to find higher-order partial derivatives --> merge mixed partial derivatives
Total differential
Determination of Differentiability of Multivariate Functions
I. definition
1. Satisfies the necessary conditions for the existence of total differentials (two first-order partial derivatives exist)
2. The equivalent form that satisfies the total differential
II. sufficient conditions for differentiability
Two first-order partial derivatives are continuous
Important content
The relationship between continuous, deflectable and differentiable
Prove several classic counterexamples
Understand the definition of total differential
Differentiation of multivariate functions
When can we use "first generation and later seeking"?
The variables with specific values in the previous generations are all variables that have nothing to do with the current derivative variable.
The derivation of a function of one variable must not be calculated first and then
Differentiation of composite functions
Unary composite function
The inner and outer layers are differentiable--->the composite function is differentiable
multivariable composite function
Derivable
Inner layer can be guided
The outer layer has continuous partial derivatives
Derivative method (chain derivative rule)
tree diagram between variables
Analyze relationships between variables
The number of derivative variables in the leaf nodes of the tree = the number of terms
The number of edges from the outermost function to the derivative variable = the number of times each factor is multiplied
Invariance of total differential form
unary function
Regardless of whether u and v are intermediate variables or independent variables, the differential form of the multivariate function f(u,v) is the same.
Implicit Function Differentiation Method
Implicit function existence theorem
If the implicit function takes the partial derivative of a certain variable ≠0---> then the variable is the dependent variable
Solve implicit function derivative OR differential
1. Invariance in total differential form (impermanence changes)
Differentiate all variables on both sides of the equation at the same time (independent variables/intermediate variables, all treated equally)
Keep whatever you want, and get rid of whatever you don’t want.
2. Find partial derivatives of the independent variables taken on both sides (constant or variable)
Draw a tree diagram between variables to clarify the relationship between variables
always changing
constant
Variables that are irrelevant to this derivative variable
variable
Variables for this derivative and variables that have a functional relationship with the variables for this derivative
3. Derivative formula of implicit function