Abstract
The discrete representation of continuous linear time-invariant signal processing systems is discussed. The orthogonal Huggins representation is introduced as an important special case of the discrete orthogonal representation. This representation uses an orthogonalized collection of complex exponentials as the orthogonal basis. Additionally, the Huggins representation of continuous linear time-invariant systems is proposed. The Huggins representation is formed as the discrete eigenfunction representation of continuous linear time-invariant systems in terms of a collection of complex exponentials. The orthogonal Huggins representation results in a quadratic computational complexity, whereas the Huggins representation yields a linear computational complexity. >
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
