研究目的
Investigating the application of neuromorphic computing in optical communications for high-speed and energy-efficient signal processing.
研究成果
Simultaneous optimization of signal shaping and neuromorphic processor enables significant gain in information transmission and relaxes requirements on complexity of signal processing.
研究不足
The study focuses on single channel operation, leaving multichannel regime to further research. The optimization of signal shaping and neuromorphic processor design is complex and requires further refinement.
1：Experimental Design and Method Selection:
The study focuses on the implementation of machine learning algorithms in the optical domain using neuromorphic computing, specifically Echo State Networks (ESN) for signal processing.
2：Sample Selection and Data Sources:
The research utilizes a single 30 Gbaud channel modulated with root-raised cosine pulses transmitted over 100 km single span with varied signal power.
3：List of Experimental Equipment and Materials:
Highly nonlinear fiber (HNLF) with specific nonlinear, dispersion, and attenuation coefficients is used.
4：Experimental Procedures and Operational Workflow:
The study involves optimizing signal shaping at the transmitter and optical processor at the receiver, comparing performance with standard linear equalization (LE) and digital back-propagation (DBP).
5：Data Analysis Methods:
Performance is quantified using bit error rate (BER) as a metric, with optimization of signal shaping and neuromorphic processor design.
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