All units combined Flashcards
Mean Value Theorem
If f : [a, b] → R is continuous on [a, b] and differentiable on (a, b), then there exists a point c ∈ (a, b) where
f’(c) = f(b) - f(a) / b - a
L’Hospital’s rule (0/0 case)
lim f’(x)/g’(x) = L
implies lim f(x)/g(x)=L
Continuous Limit Theorem
Let (fn) be a sequence of functions defined on A ⊆ R that converges uniformly on A to a function f. If each fn is continuous at c ∈ A, then f is continuous at c.
Intermediate Value Property
A function f has the intermediate value property on an
interval [a, b] if for all x < y in [a, b] and all L between f(x) and f(y), it is always possible to find a point c ∈ (x, y) where f(c) = L.
Differentiability
Let g : A → R be a function defined on an interval A. Given c ∈ A, the derivative of g at c is defined by
g’(c) = lim g(x) - g(c) / x - c
Pointwise convergence
For each n ∈ N, let fn be a function defined on a set A ⊆ R.
The sequence (fn) of functions converges pointwise on A to a function f if, for all x ∈ A, the sequence of real numbers fn(x) converges to f(x)
Uniform convergence of functions
Let (fn) be a sequence of functions defined on a set A ⊆ R. Then, (fn) converges uniformly on A to a limit
function f defined on A if, for every ϵ > 0, there exists an N ∈ N such that
|fn(x) − f(x)| < ϵ whenever n ≥ N and x ∈ A
pointwise and uniform convergence of a series
For each n ∈ N, let fn and f be functions defined on a set A ⊆ R. The infinite series converges pointwise on A to f(x) if the sequence sk(x) of partial sums defined by
sk(x) = f1(x) + f2(x) + ··· + fk(x)
converges pointwise to f(x)
The series converges uniformly on A to f if the sequence sk(x) converges uniformly on A to f(x).
power series
f(x) = Σan * x^n = a0 + a1x + a2x^2 + a3x^3
from n = 0 to n = ∞
Taylor series (Taylor’s formula)
f(x) = a0 + a1x + a2x^2 + a3x^3 + a4x^4
where an = f^n(0) / n! (the nth derivative)
Partition
A partition P of [a, b] is a finite set of points from [a, b] that includes both a and b. The notational convention is to always list the points of a partition P = {x0, x1, x2,…,xn} in increasing order
thus,
a = x0 < x1 < x2 < ··· < xn = b.
Refinement
A partition Q is a refinement of a partition P if Q contains all of the points of P; that is, if P ⊆ Q.
higher integrals
Let P be the collection of all possible partitions of the
interval [a, b].
The upper integral of f is defined to be
U(f) = inf{U(f,P) : P ∈ P}
lower integrals
Let P be the collection of all possible partitions of the
interval [a, b]
In a similar way, define the lower integral of f by
L(f) = sup{L(f,P) : P ∈ P}.
Riemann Integrability
A bounded function f defined on the interval [a, b] is Riemann-integrable if U(f) = L(f). In this case, we define ∫f or ∫f(x)dx to be this common value.
∫f = U(f) = L(f)
Interior Extremum Theorem PROOF
Theorem:
Let f be differentiable on an open interval (a, b). If f attains a maximum value at some point c ∈ (a, b)
(i.e., f(c) ≥ f(x) for all x ∈ (a, b)), then f’(c)=0. The same is true if f(c) is a minimum value.
.
Proof:
.
Because c is in the open interval (a, b), we can construct two sequences (xn) and (yn), which converge to c and satisfy xn
Continuous Limit Theorem PROOF
Theorem:
Let (fn) be a sequence of continuous functions defined on A ⊆ R that converges uniformly on A to a function f. If each fn is continuous at c ∈ A, then f is continuous at c.
.
Proof:
.
Fix c ∈ A and let ϵ > 0. Choose N so that
|fN(x) − f(x)| < ϵ/3
for all x ∈ A. Because fN is continuous, there exists a δ > 0 for which
|fN(x) − fN(c)| < ϵ/3
is true whenever |x − c| < δ. But this implies
|f(x) − f(c)|
= |f(x) − fN(x) + fN(x) − fN(c) + fN(c) − f(c)|
≤ |f(x) − fN(x)|+|fN(x) − fN(c)|+|fN(c) − f(c)|
< ϵ/3 + ϵ/3 + ϵ/3 = ϵ
Characterization of Compactness in R PROOF
A set K ⊆ R is compact if and only if it is closed and bounded
Let K be compact. We will first prove that K must be bounded, so assume, for contradiction, that K is not a bounded set. The idea is to produce a sequence in K that marches off to infinity in such a way that it cannot have a convergent subsequence as the definition of compact requires. To do this, notice that because K is not bounded there must exist an element x1 ∈ K satisfying |x1| > 1. Likewise, there must exist x2 ∈ K with |x2| > 2, and in general, given any n ∈ N, we can produce xn ∈ K such that |xn| > n.
Now, because K is assumed to be compact, (xn) should have a convergent subsequence (xnk). But the elements of the subsequence must satisfy |xnk| > nk, and consequently (xnk) is unbounded. Because convergent sequences are bounded (Theorem 2.3.2), we have a contradiction. Thus, K must at least be a bounded set.
Next, we will show that K is also closed. To see that K contains its limit points, we let x = lim xn, where (xn) is contained in K and argue that x must be in K as well. By Definition 3.3.1, the sequence (xn) has a convergent subsequence (xnk), and by Theorem 2.5.2, we know (xnk) converges to the same limit x. Finally, Definition 3.3.1 (A set K ⊆ R is compact if every sequence in K has a subsequence that converges to a limit that is also in K) requires that x ∈ K. This proves that K is closed
Baire’s Theorem PROOF
The set of real numbers R cannot be
written as the countable union of nowhere-dense sets
To start, assume that E1, E2, E3, . . . are each nowhere-dense and satisfy R = infinite union of En
By the definition of En being nowhere-dense, the closure En contains no nonempty open intervals meaning we can apply Exercise 3.5.5 to conclude that the infinite union of En-closure is not equal to R
Since each En is a subset of En-closure, then we know that the infinite untion of En is also not equal to R, which is a contradiction
Uniform Continuity of Compact Sets
A function that is continuous on a compact set K is uniformly continuous on K.
Assume f : K → R is continuous at every point of a compact set K ⊆ R.
To prove that f is uniformly continuous on K we argue by contradiction.
By the criterion in Theorem 4.4.5, if f is not uniformly continuous on K, then there exist two sequences (xn) and (yn) in K such that lim |xn − yn| = 0 while |f(xn) − f(yn)| ≥ ε0 for some particular
ε0 > 0. Because K is compact, the sequence (xn) has a convergent subsequence (xnk) with x = lim xnk also in K.
We could use the compactness of K again to produce a convergent subsequence of (yn), but notice what happens when we consider the particular subsequence (ynk) consisting of those terms in (yn) that correspond to the terms in the convergent subsequence (xnk). By the Algebraic Limit Theorem,
lim(ynk) = lim((ynk − xnk) + xnk) = 0 + x.
The conclusion is that both (xnk) and (ynk) converge to x ∈ K. Because f isassumed to be continuous at x, we have lim f(xnk) = f(x) and lim f(ynk) = f(x), which implies lim(f(xnk) − f(ynk)) = 0.
A contradiction arises when we recall that (xn) and (yn) were chosen to satisfy
|f(xn) − f(yn)| ≥ ε0
for all n ∈ N. We conclude, then, that f is indeed uniformly continuous on K
Cantor Set
a set Cn consisting of 2^n closed intervals each having length 1/(3^&n). Finally, we define the Cantor set C (Fig. 3.1) to be the intersection of all the Cns
Properties:
C is uncountable
C contains only the endpoints of each sub interval
C is a perfect set
open set
A set O ⊆ R is open if for all points a ∈ O there exists an ε-neighborhood Vε(a) ⊆ O
limit point
A point x is a limit point of a set A if every ε-neighborhood Vε(x) of x intersects the set A at some point other than x.
x is quite literally the limit of a sequence in A
isolated point
A point a ∈ A is an isolated point of A if it is not a limit point of A
closed set
A set F ⊆ R is closed if it contains its limit points
closure
Given a set A ⊆ R, let L be the set of all limit points of A. The closure of A is defined to be A-closure = A ∪ L.
complement
Ac = {x ∈ R : x /∈ A}.
A set O is open if and only if Oc is closed. Likewise, a set F is closed if and only if Fc is open
compact set
A set K ⊆ R is compact if and only if it is closed and bounded.
open cover
An open cover for A is a (possibly infinite) collection of open sets {Oλ : λ ∈ Λ} whose union contains the set A; that is, A ⊆ UOλ.
Given an open cover for A, a finite subcover is a finite subcollection of open sets from the original open cover whose union still manages to completely contain A.
A set is compact if every open cover of A contains a finite subcover of A
perfect set
A set P ⊆ R is perfect if it is closed and contains no isolated points.
Closed intervals (other than the singleton sets [a, a]) serve as the most
obvious class of perfect sets, but there are more interesting examples.
separated sets
Two nonempty sets A, B ⊆ R are separated if A-closure ∩ B and
A ∩ B-closure are both empty
connected sets
A set that is not disconnected is called a connected set.
disconnected set
A set E ⊆ R is disconnected if it can be written as E = A ∪ B, where A and B are nonempty separated sets.
Fσ sets
A set A ⊆ R is called an Fσ set if it can be written as the countable union of closed sets
Gd set
A set B ⊆ R is called a Gd set if it can be
written as the countable intersection of open sets.
nowhere-dense sets
A set E is nowhere-dense if E-closure contains no nonempty open intervals.
limit of a function
Let f : A → R, and let c be a limit
point of the domain A. We say that limx→c f(x) = L provided that, for all
ε > 0, there exists a δ > 0 such that whenever 0 < |x − c| < δ (and x ∈ A) it
follows that |f(x) − L| < ε
continuous
A function f : A → R is continuous at a
point c ∈ A if, for all ε > 0, there exists a
δ > 0 such that whenever |x − c| < δ
(and x ∈ A) it follows that
|f(x) − f(c)| < ε
If f is continuous at every point in the domain A, then we say that f is continuous on A
uniform continuity
A function f : A → R is uniformly
continuous on A if for every ε > 0 there exists a δ > 0 such that for all x, y ∈ A,
|x − y| < δ implies |f(x) − f(y)| < ε
intermediate value property
A function f has the intermediate value property on an interval [a, b] if for all
x < y in [a, b] and all L between f(x) and f(y), it is always possible to find a point c ∈ (x, y) where f(c) = L
sets of discontinuity (Df)
Given a function f : R → R, define Df ⊆ R to be the set of points where the function f fails to be continuous
monotone, increasing, decreasing functions
A function f : A → R is increasing on A if f(x) ≤ f(y) whenever x < y
decreasing if f(x) ≥ f(y) whenever x < y
A monotone function is one that is either increasing or decreasing.
removable discontinuity
If limx→c f(x) exists but has a value different from f(c), the discontinuity
at c is called removable
jump discontinuity
If limx→c+ f(x) =/= limx→c− f(x),
then f has a jump discontinuity at c
essential discontinuity
If limx→c f(x) does not exist for some other reason, then the discontinuity
at c is called an essential discontinuity.
α-continuous
Let f be defined on R, and let α > 0. The function f is α-continuous at x ∈ R if there exists a δ > 0 such that for all y, z ∈ (x−δ, x+δ) it follows that |f(y) − f(z)| < α
Df-α
Df-alpha = {x ∈ R : f is not α-continuous at x}.
Characterization of Compactness in R
A set K ⊆ R is compact if and only if it is closed and bounded