Article Details

Abstract

Signal encoding is the cornerstone of digital information transmission and processing. This paper explores a novel encoding method utilizing nonlinear dynamical systems. Within the FitzHugh-Nagumo (FHN) neuron system framework, input parameters are tuned to induce a four-level bifurcation in output responses. Building upon traditional Amplitude Shift Keying (ASK) binary encoding, this approach leverages the nonlinear dynamical characteristics of the FHN system to perform threshold subdivision on high and low level regions. Based on the relative intensity of response amplitudes, the original binary states are finely partitioned into four discrete output states (0, 1, 2, 3). This encoding mechanism fully exploits the complex dynamical behaviors of nonlinear systems, providing a new pathway to enhance channel capacity and transcend traditional binary encoding.

Keywords

FHN neuron model; encoding; amplitude shift keying; steady state; limit cycle

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About the authors

Zhang Wenjing (2001-), female, Han ethnicity, from Dezhou, Shandong, is a master's student with a research focus on nonlinear dynamics; Corresponding author: Yang Bo (1987-), male, Bai ethnic, from Kunming, Yunnan, associate professor, PhD, research direction: applied mathematics.