arXiv subjects

Ellison Murray

Publications and source records attributed to Ellison Murray.

3 recordsLinked to original sources

arXiv2026

Sparse Solution Trade-offs in GMP DPD: A Least Squares Thresholding Approach

Power amplifiers (PAs) in satellite communication systems introduce nonlinear distortion, degrading spectral fidelity. Digital pre-distortion linearizes the PA response, but full-complexity solutions are prohibitive under strict size, weight, and power (SWaP) constraints. We propose the use of Least Squares Thresholding (LST) and compare it against Orthogonal Matching Pursuit (OMP) and Matching Pursuit. LST achieves a 2.77x complexity reduction while maintaining near-identical linearization performance to OMP.

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arXiv2025

A Low-Complexity Speech Codec Using Parametric Dithering for ASR

Dithering is a technique commonly used to improve the perceptual quality of lossy data compression. In this work, we analytically and experimentally justify the use of dithering for ASR input compression. We formalize an understanding of optimal ASR performance under lossy input compression and leverage this to propose a parametric dithering technique for a low-complexity speech compression pipeline. The method performs well at 1-bit resolution, showing a 25\% relative CER improvement, while also demonstrating improvements of 32.4\% and 33.5\% at 2- and 3-bit resolution, respectively, with our second dither choice yielding a reduced data rate. The proposed codec is adaptable to meet performance targets or stay within entropy constraints.

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arXiv2025

Optimizing Audio Compression Through Entropy-Controlled Dithering

This paper explores entropy-controlled dithering techniques in audio compression, examining the application of standard and modified TPDFs, combined with noise shaping and entropy-controlled parameters, across various audio contexts, including pitch, loudness, rhythm, and instrumentation variations. Perceptual quality metrics such as VISQOL and STOI were used to evaluate performance. The results demonstrate that TPDF-based dithering consistently outperforms RPDF, particularly under optimal alpha conditions, while highlighting performance variability based on signal characteristics. These findings suggest the situational appropriateness of using various TPDF distributions. This work emphasizes the trade-off between entropy and perceptual fidelity, offering insights into the potential of entropy-controlled dithering as a foundation for enhanced audio compression algorithms. A practical implementation as a Digital Audio Workstation plugin introduces customizable dithering controls, laying the groundwork for future advancements in audio compression algorithms.

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