A matrix-multiplying ADC implementing a machine-learning classifier directly with data conversion

Jintao Zhang, Zhuo Wang, Naveen Verma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

25 Scopus citations

Abstract

Embedded sensing systems conventionally perform A-to-D conversion followed by signal analysis. In many applications, the analysis of interest is inference (e.g., classification), but the sensor signals involved are too complex to model analytically. Machine learning is gaining prominence because it enables data-driven training of classifiers, overcoming the need for analytical models. This work presents: 1) an algorithmic formulation, where feature extraction and classification are combined into a single matrix, reducing the total multiplications needed, and 2) a matrix-multiplying ADC (MMADC) that enables multiplication of input samples by a programmable matrix. Thus, the MMADC combines feature extraction and classification with data conversion, mitigating the need for further computations. Two systems are demonstrated: an ECG-based cardiac-arrhythmia detector and an image-pixel-based gender detector.

Original languageEnglish (US)
Title of host publication2015 IEEE International Solid-State Circuits Conference, ISSCC 2015 - Digest of Technical Papers
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages332-333
Number of pages2
ISBN (Electronic)9781479962235
DOIs
StatePublished - Mar 17 2015
Event2015 62nd IEEE International Solid-State Circuits Conference, ISSCC 2015 - Digest of Technical Papers - San Francisco, United States
Duration: Feb 22 2015Feb 26 2015

Publication series

NameDigest of Technical Papers - IEEE International Solid-State Circuits Conference
Volume58
ISSN (Print)0193-6530

Other

Other2015 62nd IEEE International Solid-State Circuits Conference, ISSCC 2015 - Digest of Technical Papers
CountryUnited States
CitySan Francisco
Period2/22/152/26/15

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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    Zhang, J., Wang, Z., & Verma, N. (2015). A matrix-multiplying ADC implementing a machine-learning classifier directly with data conversion. In 2015 IEEE International Solid-State Circuits Conference, ISSCC 2015 - Digest of Technical Papers (pp. 332-333). [7063061] (Digest of Technical Papers - IEEE International Solid-State Circuits Conference; Vol. 58). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISSCC.2015.7063061