Researchers Characterize Error in Hadamard Transform for Convolution

Ben Fauber, Alireza Moradzadeh· July 20, 2026 View original

Summary

A new paper characterizes the algebraic error introduced when substituting the Hadamard transform for the Discrete Fourier Transform in computing circular convolution. The research identifies universal error-free positions, describes the error operator's rank, and provides a closed-form expression for the expected error, showing it can double output energy except for specific filters.

This research delves into the algebraic error that arises when the Hadamard transform is used as a substitute for the Discrete Fourier Transform (DFT) in computing circular convolution. While the Hadamard transform is often preferred for its real-valued sign flips and computational efficiency, this substitution introduces a quantifiable error. The paper presents three key findings that characterize this error. Firstly, it identifies specific input and output positions where the error universally cancels out, meaning these positions are always error-free. Secondly, the error operator is shown to be nearly full rank, indicating a broad impact, with its null space having only logarithmic dimension. Lastly, the expected error is found to be governed by a single alignment scalar, for which a closed-form expression is derived by averaging over random filters. The findings collectively reveal that this substitution error is structured, predictable, and can asymptotically double the output energy, except for specific filters that reside in the universal zero-error subspace.

Why it matters

For engineers and researchers working with signal processing, image processing, or data analysis involving convolutions, understanding this error is crucial for choosing appropriate transforms and ensuring accuracy in applications where computational efficiency is balanced against precision.

How to implement this in your domain

  1. 1Review existing signal processing pipelines that utilize Hadamard transforms for convolution.
  2. 2Assess the potential impact of the identified algebraic error on application accuracy.
  3. 3Consider implementing error characterization techniques to quantify the error in specific use cases.
  4. 4Explore strategies to mitigate error, such as leveraging the identified error-free subspaces or applying correction factors.
  5. 5Educate engineering teams on the trade-offs between computational efficiency and accuracy when selecting transforms.

Who benefits

TelecommunicationsSignal ProcessingImage ProcessingData ScienceScientific Computing

Key takeaways

  • Substituting Hadamard for DFT in convolution introduces structured algebraic error.
  • Specific input/output positions are universally error-free.
  • The error operator is nearly full rank, impacting most outputs.
  • The error can asymptotically double output energy, except for specific filters.

Original post by Ben Fauber, Alireza Moradzadeh

"arXiv:2607.15293v1 Announce Type: new Abstract: Dyadic and circular convolution can both be computed in $O(N\log N)$ time using the Hadamard transform and the FFT-computed discrete Fourier transform (DFT), respectively. The Hadamard transform is preferable for its real-valued sig…"

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Originally posted by Ben Fauber, Alireza Moradzadeh on X · view source

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