As the demand for faster, more efficient training of neural networks continues to grow, specialized photonic hardware has emerged as a potential alternative to classical computers for AI applications. Reservoir Computing (RC), a lightweight alternative to computationally-intensive Recurrent Neural Networks, has been demonstrated to be possible using simple delay dynamical systems. We propose an optoelectronic implementation of this architecture through a Mach-Zehnder modulator driven by delayed feedback from a laser. We introduce a new optoelectronic scheme in which input data is first pre...
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