Version 1
: Received: 29 April 2020 / Approved: 30 April 2020 / Online: 30 April 2020 (16:39:39 CEST)
How to cite:
Liu, G.; Wang, J. A Novel System Analysis Methodology: Transform Method, Relation Spectrum, and System Filter. Preprints2020, 2020040538. https://doi.org/10.20944/preprints202004.0538.v1
Liu, G.; Wang, J. A Novel System Analysis Methodology: Transform Method, Relation Spectrum, and System Filter. Preprints 2020, 2020040538. https://doi.org/10.20944/preprints202004.0538.v1
Liu, G.; Wang, J. A Novel System Analysis Methodology: Transform Method, Relation Spectrum, and System Filter. Preprints2020, 2020040538. https://doi.org/10.20944/preprints202004.0538.v1
APA Style
Liu, G., & Wang, J. (2020). A Novel System Analysis Methodology: Transform Method, Relation Spectrum, and System Filter. Preprints. https://doi.org/10.20944/preprints202004.0538.v1
Chicago/Turabian Style
Liu, G. and Jing Wang. 2020 "A Novel System Analysis Methodology: Transform Method, Relation Spectrum, and System Filter" Preprints. https://doi.org/10.20944/preprints202004.0538.v1
Abstract
We have presented a controllable and human-readable polynomial neural network (CR-PNN) that is the first human-readable neural network. One can imagine its influence on system identification. Subsequently, we developed a relation spectrum in a medical application, which is likely to stand alongside the Fourier spectrum. However, the system analysis methodology is incomplete in contrast to signal processing methodology. Here, we presented the system filters for the first time. In this paper, we used the simulation system to verify the availability of the system analysis methodology. The system analysis methodology showed great properties in system identification and filter. The contribution of this paper is the system analysis methodology: transform method (CR-PNN), relation spectrum, and system filter design.
CR-PNN; relation spectrum; system identification; system filters; transfer function
Subject
Engineering, Control and Systems Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
