Victor E. DeBrunner — accepted AI-conference papers

2023

Fast Convolution Algorithm for Real-Valued Finite Length Sequences

Weiwei Wang, Victor E. DeBrunner, Linda S. DeBrunner

ICASSP 2023accepted

The Fast Fourier Transform (FFT)-based convolution is the most popular fast convolution algorithm. In past work, we developed the Discrete Hirschman Transform (DHT)-based convolution. When compared to the FFT-based convolution, our DHT-based convolution can reduce the computational complexity by a t…

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2015

A proof of Hirschman Uncertainty invariance to the order of Rényi entropy for Picket Fence signals, and its relevance in a simplistic recognition experiment

Kirandeep Ghuman, Victor E. DeBrunner

ICASSP 2015accepted

In [1] we developed a new uncertainty measure which incorporates Rényi entropy instead of Shannon entropy. This new uncertainty measure was conjectured to be invariant to the Rényi order α > 0 for the case of the optimizer signals of Hirschman Uncertainty (Picket Fence functions whose lengths are a…

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