Frame Multiplication Theory and a Vector-Valued DFT and Ambiguity Function
Frame Multiplication Theory and a Vector-Valued DFT and Ambiguity Function
复制标题
帧乘法理论以及向量值DFT和模糊度函数
DOI:
10.1007/s00041-018-09653-x
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发表时间:
2019
影响因子:
1.2
通讯作者:
Donatelli, Jeffrey J.
中科院分区:
文献类型:
--
作者:
Andrews, Travis D.;Benedetto, John J.;Donatelli, Jeffrey J.
Vector-valued discrete Fourier transforms (DFTs) and ambiguity functions are defined. The motivation for thedefinitionsis to provide realistic modeling of multi-sensor environments in which a useful time–frequency analysis is essential. The definition of the DFT requires associateduncertainty principle inequalities. The definition of the ambiguity function requires a component that leads to formulating a mathematical theory in which two essential algebraic operations can be made compatible in a natural way. The theory is referred to asframe multiplication theory. These definitions, inequalities, and theory are interdependent, and they are the content of the paper with the centerpiece being frame multiplication theory. The technology underlying frame multiplication theory is the theory of frames, short time Fourier transforms, and the representation theory of finite groups. The main results have the following form: frame multiplication exists if and only if the finite frames that arise in the theory are of a certain type, e.g., harmonic frames, or, more generally, group frames. In light of the complexities and the importance of the modeling of time-varying and dynamical systems in the context of effectively analyzing vector-valued multi-sensor environments, the theory of vector-valued DFTs and ambiguity functions must not only bemathematically meaningful, but it must haveconstructive implementable algorithms, and becomputationally viable. This paper presents our vision for resolving these issues, in terms of a significant mathematical theory, and based on the goal of formulating and developing a useful vector-valued theory.
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影响因子:
1.7
作者:
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影响因子:
0.6
作者:
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DOI:
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发表时间:
2008
期刊:
2008 42nd Asilomar Conference on Signals, Systems and Computers
影响因子:
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影响因子:
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作者:
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期刊:
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