Edoardo Provenzi - From Euclidean to Hilbert Spaces

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From Euclidian to Hilbert Spaces analyzes the transition from finite dimensional Euclidian spaces to infinite-dimensional Hilbert spaces, a notion that can sometimes be difficult for non-specialists to grasp. The focus is on the parallels and differences between the properties of the finite and infinite dimensions, noting the fundamental importance of coherence between the algebraic and topological structure, which makes Hilbert spaces the infinite-dimensional objects most closely related to Euclidian spaces.<br /><br />The common thread of this book is the Fourier transform, which is examined starting from the discrete Fourier transform (DFT), along with its applications in signal and image processing, passing through the Fourier series and finishing with the use of the Fourier transform to solve differential equations.<br /><br />The geometric structure of Hilbert spaces and the most significant properties of bounded linear operators in these spaces are also covered extensively. The theorems are presented with detailed proofs as well as meticulously explained exercises and solutions, with the aim of illustrating the variety of applications of the theoretical results.

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From Euclidean to Hilbert Spaces - фото 17

and:

2 symmetrical v w w v v w V 3 defined v v 0 v - фото 18

2) symmetrical:v, w 〉 = 〈 w, v 〉, ∀ v, wV ;

3) defined:v, v 〉 = 0 картинка 19 v = 0 V, the null vector of the vector space V ;

4) positive:v, v 〉 > 0 ∀ vV , v ≠ 0 V.

Upon reflection, we see that, for a real form over V , the symmetry and bilinearity requirements are equivalent to requiring symmetry and linearity on the left-hand side , that is:

The simplest and most important example of a real inner product is the - фото 20

The simplest and most important example of a real inner product is the canonical inner product , defined as follows: let v = ( v 1, v 2, . . . , v n), w = ( w 1, w 2, . . . , w n) be two vectors in ℝ nwritten with their components in relation to any given, but fixed, basis From Euclidean to Hilbert Spaces - изображение 21in ℝ n. The canonical inner product of v and w is:

where v tand w tin the final equations are the transposed vectors of v and w - фото 22

where v tand w tin the final equations are the transposed vectors of v and w , giving us the matrix product of a line vector (treated as a 1 × n matrix) and a column vector (treated as an n × 1 matrix).

The extension of these definitions to complex vector spaces is not particularly straightforward. First, note that if V is a complex vector space, then there is no bilinear and definite-positive transformation over V × V . In this case, any vector vV would give the following:

As we shall see the property of positivity is essential in order to define a - фото 23

As we shall see, the property of positivity is essential in order to define a norm (and thus a distance, and by extension, a topology) from a complex inner product. To obtain an algebraic structure for complex scalar products which remains compatible with a topological structure, we are therefore forced to abandon the notion of bilinearity, and to search for an alternative.

We could consider antilinearity 2, i.e.

From Euclidean to Hilbert Spaces - изображение 24

But it has the same problem as bilinearity, 〈 iv, iv 〉 = (− i )(− i )〈 v, v 〉 = i 2〈 v, v 〉 = −〈 v, v 〉 2≼ 0.

A simple analysis shows that, in order to avoid losing the positivity, it is sufficient to request the linearity with respect to one variable and the antilinearity with respect to the other. This property is called sesquilinearity 3.

The choice of the linear and antilinear variable is entirely arbitrary.

By convention, the antilinear component is placed on the right-hand side in mathematics, but on the left-hand side in physics.

We have chosen to adopt the mathematical convention here, i.e. 〈 αv, βw 〉 = α β̅v, w 〉.

Next, it is important to note that sesquilinearity and symmetry are incompatible : if both properties were verified, then 〈 v, αw 〉 = картинка 25v, w 〉, and also 〈 v, αw 〉 = 〈 αw, v 〉 = αw, v 〉 = αv, w 〉. Thus, 〈 v, αw 〉 = картинка 26v, w 〉 = αv, w 〉 which can only be verified if α ∈ ℝ.

Thus 〈, 〉 cannot be both sesquilinear and symmetrical when working with vectors belonging to a complex vector space.

The example shown above demonstrates that, instead of symmetry, the property which must be verified for every vector pair v, w is From Euclidean to Hilbert Spaces - изображение 27, that is, changing the order of the vectors in 〈, 〉 must be equivalent to complex conjugation.

A transform which verifies this property is said to be Hermitian 4.

These observations provide full justification for Definition 1.3.

DEFINITION 1.3.– Let V be a complex vector space. The pair ( V , 〈, 〉) is said to be a complex inner product space (or a complex pre-Hilbert space) if 〈, 〉 is a complex form which is:

1) sesquilinear:

v 1 v 2 w 1 w 2 V and α β - фото 28

v 1, v 2, w 1, w 2∈ V , and:

α β v w V 2 Hermitian - фото 29

α, βFrom Euclidean to Hilbert Spaces - изображение 30, ∀ v, wV ;

2) Hermitian: From Euclidean to Hilbert Spaces - изображение 31, ∀ v, wV ;

3) definite:v, v 〉 = 0 картинка 32 v = 0 V, the null vector of the vector space V ;

4) positive:v, v 〉 > 0 ∀ vV , v ≠ 0 V.

As in the case of the canonical inner product, for a complex form over V , the symmetry and sesquilinearity requirement is equivalent to requiring the Hermitian property and linearity on the left-hand side ; if these properties are verified, then:

Considering the sum of n rather than two vectors sesquilinearity is - фото 33

Considering the sum of n , rather than two, vectors, sesquilinearity is represented by the following formulae:

[1.1] 12 In n the complex Euclidean inner product - фото 34

[1.2] In n the complex Euclidean inner product is defined by - фото 35

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