Main concepts and properties. Examples of normed spaces
[18/17%]Prove Young's inequality: , where , and . Prove that equality is attained if and only if .
Let be a measure space with a sigma-finite measure, and let the measurable functions and be integrable on with respect to the measure to the powers and respectively, . Prove the integral Hölder inequality
Prove that equality is attained if and only if the functions and are linearly dependent.
Let be a measure space with a sigma-finite measure, and let the measurable functions and be integrable on with respect to the measure to the power . Prove the integral Minkowski inequality
Prove that for equality in the integral Minkowski inequality is attained if and only if the functions and are linearly dependent.
Devise measure spaces for which inequalities (2.1) and (2.2) turn into the numerical Hölder and Minkowski inequalities :
Give examples of measurable functions such that:
;
belongs to , but is not bounded on .
For functions prove the inequality .
Prove that if and the measure is finite, then . In particular, for any vector it holds that
Verify the axioms of a norm in the spaces (see the list of spaces):
;
;
,
;
;
;
;
.
Prove that the norms and , introduced on the space in the list of spaces, satisfy the axioms of a norm and are equivalent.
Among the mappings of the linear space of continuously differentiable functions on the segment [ 0,1 ] listed below, choose the mappings satisfying the axioms of a norm, and order these norms with respect to the subordination relation:
;
;
;
, where ;
;
, where .
Let the function be continuous and positive on . Prove that the mapping , acting from to , where , satisfies the axioms of a norm, and this norm is equivalent to the standard .
Verify the axioms of a norm on the space of functions of bounded variation .
Prove that all norms , where , on the space of functions of bounded variation are equivalent to each other and equivalent to the norm from the list of spaces.
Verify the axioms of a norm in the space (see the list of spaces).
Prove Theorem 2.1 on the equivalence of norms in a finite-dimensional space.
Theorem 2.1: If (here is the linear dimension of the linear space ) and and are two different norms on , then , i.e., there exist constants such that for all .
Let be a numerical function on a linear space satisfying the first two axioms of a norm. Prove that the third axiom (the triangle inequality) is equivalent to the convexity of the set .
Prove that the function is not a norm for on an -dimensional linear space for . .
Find and , where , for all and ,
Prove that in the linear space , the norms and , are not equivalent, but .
Prove that the norms and , in the linear space of continuous functions on are not equivalent, but .