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ICANN
2010
Springer

Designing Simple Nonlinear Filters Using Hysteresis of Single Recurrent Neurons for Acoustic Signal Recognition in Robots

11 years 7 months ago
Designing Simple Nonlinear Filters Using Hysteresis of Single Recurrent Neurons for Acoustic Signal Recognition in Robots
Abstract. In this article we exploit the discrete-time dynamics of a single neuron with self-connection to systematically design simple signal filters. Due to hysteresis effects and transient dynamics, this single neuron behaves as an adjustable low-pass filter for specific parameter configurations. Extending this neuro-module by two more recurrent neurons leads to versatile high- and band-pass filters. The approach presented here helps to understand how the dynamical properties of recurrent neural networks can be used for filter design. Furthermore, it gives guidance to a new way of implementing sensory preprocessing for acoustic signal recognition in autonomous robots. Key words: Neural networks, Digital signal processing, Non-speech recognition, Autonomous robots, Walking robots
Poramate Manoonpong, Frank Pasemann, Christoph Kol
Added 09 Nov 2010
Updated 09 Nov 2010
Type Conference
Year 2010
Where ICANN
Authors Poramate Manoonpong, Frank Pasemann, Christoph Kolodziejski, Florentin Wörgötter
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