How to prove Schwartz Inequality?

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In summary, the Schwartz Inequality states that for any non-zero vectors u and v, the Hermitian product <u,v> is less than or equal to the product of the norms of u and v. This can be proven by assuming u and v are non-zero, and then using the Pythagorean theorem and the orthogonality condition to show that <u,v> squared is less than or equal to the product of the norms of u and v squared.
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Homework Statement



Prove the Schwartz Inequality

/<u, v>/ is < or = //u//*//v//

for the Hermitian product.

Homework Equations


The Attempt at a Solution



Assume u, v are non-zero. For any r, s exist in set of complex numbers, //rv + su// is > or = 0. Then, //rv + su//^2 = <rv+su, rv+su> = <rv, rv> + <rv, su> + <su, rv> + <su, su> = r^2<v, v> + rs <v, u> + sr <u, v> + s^2 <u, u> is > or = 0

Not sure where to go from there...set r = <u u> and s = ...?? I don't know.

Note: I was working off of the proof of the inequality for the dot product. I am just not sure how the Hermitian properties affect it. is <v, u> = <u, v>, etc.
 
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We say (u.v)2 ≤ |u|2 |v|2, then if u or v = 0 then both sides of both sides are zero. But if they are not zero, the vector v can be rewritten as the sum of some scalar multiple of u, ku, and a vector w that is orthogonal to u. The k is obtained by w = v-ku & the orthogonality condition u.w=0

0 = u.w = u.(v-ku) = (u.v)-k(u.u), it follows that k = u.v/u.u, now apply the pythagoras theorem:

|v|2 = |ku|2 + |w|2 = k|u|2 + |w|2

|u|2|v|2 = (u.v) + |u|2|w|2

since |u|2|w|2 ≥ 0, you have (u.v)2 ≤ |u|2 |v|2
This establishes what we said first and hence the cauchy shwartz inequality.
 

1. What is Schwartz Inequality?

Schwartz Inequality, also known as Cauchy-Schwarz Inequality, is a mathematical concept used to prove the relationship between two vectors in an inner product space. It states that the dot product of two vectors is less than or equal to the product of their magnitudes.

2. How is Schwartz Inequality used?

Schwartz Inequality is used in various mathematical fields, such as linear algebra, analysis, and statistics, to prove the relationship between two vectors. It is also used to prove other mathematical theorems and inequalities.

3. What is the proof of Schwartz Inequality?

The proof of Schwartz Inequality involves using the properties of inner product spaces, such as positivity, linearity, and symmetry, to show that the dot product of two vectors is less than or equal to the product of their magnitudes. This proof is commonly seen in textbooks and mathematical proofs.

4. Can Schwartz Inequality be applied to any type of vectors?

Yes, Schwartz Inequality can be applied to any type of vectors in an inner product space, as long as the inner product is defined for those vectors. This includes vectors in Euclidean space, function spaces, and more.

5. Are there any real-life applications of Schwartz Inequality?

Yes, Schwartz Inequality has many real-life applications, particularly in statistics and data analysis. It is used to prove various statistical theorems and inequalities, such as the correlation coefficient and the Cauchy-Schwarz Master Theorem. It is also used in machine learning and signal processing algorithms.

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