期刊
PHYSICA D-NONLINEAR PHENOMENA
卷 239, 期 12, 页码 905-911出版社
ELSEVIER
DOI: 10.1016/j.physd.2009.11.015
关键词
Auditory system; Neural oscillation; Canonical model; Network dynamics; Nonlinear resonance
资金
- Direct For Social, Behav & Economic Scie
- Division Of Behavioral and Cognitive Sci [1362417] Funding Source: National Science Foundation
We derive a canonical model for gradient frequency neural networks (GENNs) capable of processing time-varying external stimuli. First, we employ normal form theory to derive a fully expanded model of neural oscillation. Next, we generalize from the single oscillator model to heterogeneous frequency networks with an external input. Finally, we define the GFNN and illustrate nonlinear time-frequency transformation of a time-varying external stimulus. This model facilitates the study of nonlinear time-frequency transformation, a topic of critical importance in auditory signal processing. (c) 2010 Elsevier B.V. All rights reserved.
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