Discrete representation of continuous signals: the Huggins transform

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.<
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