Mathematical methods for signal and image treatment : Appendices

Appendices
Mathematical methods for signal and image treatment

Author : Bruno TORRÉSANI

Publication date: October 10, 2011 | Lire en français

Add to my library

7. Appendices

7.1 Signal vector spaces

Signals of a given length N are frequently represented as vectors, i.e. as elements of the space $ℂ^{N}$ (or $ℝ^{N}$ in the real case). This choice makes it possible to associate any two signals $x, y \in ℂ^{N}$ with their "scalar product".

You do not have access to this resource.

Exclusive to subscribers. 97% yet to be discovered!

You do not have access to this resource. Click here to request your free trial access!

Already subscribed? Log in!

Ongoing reading
Appendices

Previous
page A new point of view: the "parsimonious path".

Bibliography

(1) - CARMONA (R.), HWANG (W.L.), TORRÉSANI (B.) - Practical Time-Frequency Analysis : continuous wavelet and Gabor transforms, with an implementation in S - volume 9 of Wavelet Analysis and its Applications. Academic Press, San Diego (1998).
(2) - DAUBECHIES (I.) - Ten...

You do not have access to this resource.

Exclusive to subscribers. 97% yet to be discovered!

You do not have access to this resource. Click here to request your free trial access!

Already subscribed? Log in!

Article included in this offer

"Mathematics"

( 168 articles )

Complete knowledge base

Updated and enriched with articles validated by our scientific committees

Services

A set of exclusive tools to complement the resources

View offer details

Appendices Mathematical methods for signal and image treatment

7. Appendices

7.1 Signal vector spaces

Bibliography

Appendices
Mathematical methods for signal and image treatment