Literature DB >> 33765073

A four-state adaptive Hopf oscillator.

XiaoFu Li1, Md Raf E Ul Shougat1, Scott Kennedy1, Casey Fendley2, Robert N Dean2, Aubrey N Beal3, Edmon Perkins1.   

Abstract

Adaptive oscillators (AOs) are nonlinear oscillators with plastic states that encode information. Here, an analog implementation of a four-state adaptive oscillator, including design, fabrication, and verification through hardware measurement, is presented. The result is an oscillator that can learn the frequency and amplitude of an external stimulus over a large range. Notably, the adaptive oscillator learns parameters of external stimuli through its ability to completely synchronize without using any pre- or post-processing methods. Previously, Hopf oscillators have been built as two-state (a regular Hopf oscillator) and three-state (a Hopf oscillator with adaptive frequency) systems via VLSI and FPGA designs. Building on these important implementations, a continuous-time, analog circuit implementation of a Hopf oscillator with adaptive frequency and amplitude is achieved. The hardware measurements and SPICE simulation show good agreement. To demonstrate some of its functionality, the circuit's response to several complex waveforms, including the response of a square wave, a sawtooth wave, strain gauge data of an impact of a nonlinear beam, and audio data of a noisy microphone recording, are reported. By learning both the frequency and amplitude, this circuit could be used to enhance applications of AOs for robotic gait, clock oscillators, analog frequency analyzers, and energy harvesting.

Entities:  

Year:  2021        PMID: 33765073      PMCID: PMC7993838          DOI: 10.1371/journal.pone.0249131

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  10 in total

1.  Finding downbeats with a relaxation oscillator.

Authors:  Douglas Eck
Journal:  Psychol Res       Date:  2002-02

2.  A learning model for oscillatory networks.

Authors:  J Nishii
Journal:  Neural Netw       Date:  1998-03

3.  Adaptive and Energy Efficient Walking in a Hexapod Robot Under Neuromechanical Control and Sensorimotor Learning.

Authors:  Xiaofeng Xiong; Florentin Worgotter; Poramate Manoonpong
Journal:  IEEE Trans Cybern       Date:  2015-09-30       Impact factor: 11.448

4.  Human-robot synchrony: flexible assistance using adaptive oscillators.

Authors:  Renaud Ronsse; Nicola Vitiello; Tommaso Lenzi; Jesse van den Kieboom; Maria Chiara Carrozza; Auke Jan Ijspeert
Journal:  IEEE Trans Biomed Eng       Date:  2010-10-25       Impact factor: 4.538

5.  FPGA implementation of a configurable neuromorphic CPG-based locomotion controller.

Authors:  Jose Hugo Barron-Zambrano; Cesar Torres-Huitzil
Journal:  Neural Netw       Date:  2013-04-12

6.  Design and Hardware Implementation of a New Chaotic Secure Communication Technique.

Authors:  Li Xiong; Yan-Jun Lu; Yong-Fang Zhang; Xin-Guo Zhang; Parag Gupta
Journal:  PLoS One       Date:  2016-08-22       Impact factor: 3.240

7.  Compact Hip-Force Sensor for a Gait-Assistance Exoskeleton System.

Authors:  Hyundo Choi; Keehong Seo; Seungyong Hyung; Youngbo Shim; Soo-Chul Lim
Journal:  Sensors (Basel)       Date:  2018-02-13       Impact factor: 3.576

8.  Fast Dynamical Coupling Enhances Frequency Adaptation of Oscillators for Robotic Locomotion Control.

Authors:  Timo Nachstedt; Christian Tetzlaff; Poramate Manoonpong
Journal:  Front Neurorobot       Date:  2017-03-21       Impact factor: 2.650

  10 in total

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