How can the Lp Norm be used to prove inequalities?

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SUMMARY

The discussion centers on the application of Lp norms to prove inequalities, specifically focusing on the relationship between the L1 norm and Lp norms for p > 1. Participants explore the inequalities (a_1 + a_2 + ... + a_N)^\alpha ≥ a_1^\alpha + a_2^\alpha + ... + a_N^\alpha and the implications of the triangle inequality in proving these relationships. The convexity of the function f = x^α is also highlighted as a key concept in deriving proofs for the inequalities presented.

PREREQUISITES
  • Understanding of Lp norms and their properties
  • Familiarity with convex functions and their implications in inequalities
  • Knowledge of the triangle inequality in normed spaces
  • Basic calculus, including partial derivatives and their applications
NEXT STEPS
  • Study the properties of Lp norms, particularly the relationship between L1 and Lp norms for p > 1
  • Learn how to apply the triangle inequality in proving inequalities involving norms
  • Explore the concept of convexity in functions and its role in mathematical proofs
  • Investigate specific examples of inequalities involving Lp norms and their proofs
USEFUL FOR

Mathematicians, students in advanced calculus or real analysis, and anyone interested in understanding the application of Lp norms in proving mathematical inequalities.

ashah99
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TL;DR
I would appreciate some help on proofs involving the Lp norm below, please. I looked up Holder's inequality, which might help with this problem, but I'm not sure how to set up the proofs.
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(a_1+a_2+a_3)^\alpha \ge a_1^\alpha+(a_2+a_3)^\alpha \ge a_1^\alpha + a_2^\alpha + a_3^\alpha
a_1+a_2+a_3 \ge [a_1^\alpha + a_2^\alpha + a_3^\alpha]^{\frac{1}{\alpha} }
and so on.

Bonus
f(x,y):=(x+y)^a-x^a-y^a
x,y \ge 0 ,\ \ a \ge 1
\frac{\partial f}{\partial x} \ge 0,\ \ \frac{\partial f}{\partial y} \ge 0, \ \ f(0,0)=0
 
Last edited:
anuttarasammyak said:
(a_1+a_2+a_3)^\alpha \ge a_1^\alpha+(a_2+a_3)^\alpha \ge a_1^\alpha + a_2^\alpha + a_3^\alpha
a_1+a_2+a_3 \ge [a_1^\alpha + a_2^\alpha + a_3^\alpha]^{\frac{1}{\alpha} }
and so on.

Bonus
f(x,y):=(x+y)^a-x^a-y^a
x,y \ge 0 ,\ \ a \ge 1
\frac{\partial f}{\partial x} \ge 0,\ \ \frac{\partial f}{\partial y} \ge 0, \ \ f(0,0)=0
How would I prove part (1)? By inspection, the l1 norm will be greater that the lp form when p > 1, since l1 is just the sum of the magnitudes...just not sure how to show work that is proof-based.

Are your hints regarding parts 2 & 3?
 
I stopped at 3 but you should continue upto N
(a_1+a_2+...+a_N)^\alpha \ge a_1^\alpha + a_2^\alpha + ... +a_N^\alpha
a_1+a_2+...+a_N \ge (a_1^\alpha + a_2\alpha + ... +a_N^\alpha)^\frac{1}{\alpha}
Let ##a_k=|x_k|##
 
anuttarasammyak said:
I stopped at 3 but you should continue upto N
(a_1+a_2+...+a_N)^\alpha \ge a_1^\alpha + a_2^\alpha + ... +a_N^\alpha
a_1+a_2+...+a_N \ge (a_1^\alpha + a_2\alpha + ... +a_N^\alpha)^\frac{1}{\alpha}
Let ##a_k=|x_k|##
I see that, how does this relate to part 1? I’m slow at understanding it seems.
 
(|x_1|+|x_2|+...+|x_N|)^p \ge |x_1|^p +|x_2|^p + ... +|x_N|^p
l_1\ norm=|x_1|+|x_2|+...+|x_N| \ge (|x_1|^p +|x_2|^p + ... +|x_N|^p)^\frac{1}{p}=l_p \ norm
 
anuttarasammyak said:
(|x_1|+|x_2|+...+|x_N|)^p \ge |x_1|^p +|x_2|^p + ... +|x_N|^p
l_1\ norm=|x_1|+|x_2|+...+|x_N| \ge (|x_1|^p +|x_2|^p + ... +|x_N|^p)^\frac{1}{p}=l_p \ norm
Okay. this makes sense. Thanks. How would part 2 be proved? I'm thinking I would need to choose some a_i and α and by using the convexity of the function f = x^α. Any thoughts here?
 
ashah99 said:
I'm thinking I would need to choose some a_i and α and by using the convexity of the function f = x^α.
Why don’t you do it ?

Also the hint may be helpful for 2 also. Try substituting ##a_k## to what ?
 
Last edited:
ashah99 said:
How would I prove part (1)? By inspection, the l1 norm will be greater that the lp form when p > 1, since l1 is just the sum of the magnitudes...just not sure how to show work that is proof-based.

Are your hints regarding parts 2 & 3?
since you know the Lp norm is a norm, you should be able to recognize that (1) is implied by triangle inequality, i.e.

##\big \Vert \mathbf x \big \Vert_p=\big \Vert \sum_{k=1}^n x_k \cdot \mathbf e_k\big \Vert_p\leq \sum_{k=1}^n \big \Vert x_k\cdot \mathbf e_k \big \Vert_p = \sum_{k=1}^n \big \Vert x_k\cdot \mathbf e_k \big \Vert_1 = \big \Vert \mathbf x \big \Vert_1##
 
  • #10
For (2), if ##q<p##, raise both sides to the ##q## power. Then you can pick a clever choice of ##y## to rewrite the inequality as ##||y||_{p/q} \leq ||y||_1##.
 

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