Emily L Yang, Liyuan Guo
Implantable neural interfaces require low-power real-time signal processing to remain within strict thermal and bandwidth constraints, motivating lightweight feature extraction methods for on-chip spike sorting. This work presents the Walsh-Hadamard Transform (WHT) as a hardware-efficient feature extraction method for neural spike classification. WHT can be implemented using only adders, subtractors, and registers without coefficient memory. WHT performance is compared against the Compressed Hadamard Transform (CHT) and Principal Component Analysis (PCA), improving mean F1-scores from 55–60% to 70–75% on difficult high-noise datasets and from 90–95% to 95–99% on all other simulated datasets. In addition to improved classification performance, WHT demonstrates greater robustness to noise, downsampling, reduced training size, and distance metric selection, maintaining standard deviations typically below 5%, while CHT and PCA reach up to 10% under high-noise conditions.
@article{443c8941-8760-4545-b35d-9dad84f22b5c,
title={Robust and Efficient Feature Extraction for Spike Sorting via the Walsh-Hadamard Transform},
author={Emily L Yang and Liyuan Guo},
year={2022},
language={en}
}TY - JOUR TI - Robust and Efficient Feature Extraction for Spike Sorting via the Walsh-Hadamard Transform AU - Emily L Yang AU - Liyuan Guo PY - 2022 LA - en ER -
This paper addresses the challenge of assessing the feasibility of wind power plant projects at sites with insufficient or no local historic wind data
Ian Cameron, Mitren Sukhram
This book delves into the intricate processes involved in blast furnace ironmaking, emphasizing the analysis, control, and optimization of operations.
Unknown, Unknown
This study focuses on the fundamental characteristics of solid iron, which is predominantly composed of iron atoms and provides a basis for understand
Siddhartha Mukherjee
This book provides a comprehensive overview of the critical aspects of industrial process engineering and plant design, addressing the complexities an
Rajesh Jha, Bimal Kumar Jha
This book describes the application of artificial intelligence (AI) and machine learning (ML) concepts to develop predictive models that can be used t
Unknown, Unknown
This chapter discusses metal casting processes, highlighting the diversity and common characteristics among them. The objective is to elucidate the fu