A reservoir computing system (RC) based on a vertical cavity surface emitting semiconductor laser (VCSEL) subject to arbitrary-polarization optical feedback is proposed, and its performance for predicting Santa-Fee time series is numerically analyzed. Taking advantage of the fact that the light emitted by VCSEL has two polarization components, a tunable polarization wave plate is placed in the feedback loop to adjust the polarization angle of the feedback light. The influences of system typical parameters on the prediction error of such a RC system have been analyzed in detail. Through optimizing the parameters of feedback strength, injection coefficient and polarization angle, the prediction error of 3% can be realized for the reservoir computing system.
Optoelectronic reservoir computing (RC) is a supervised training algorithm implanted in an optoelectronic time-delay system, which possesses simple structure and can be utilized to realize pattern recognition. In this work, based on double reservoir layers composed of two Mach-Zehnder modulators (MZMs), a novel optoelectronic RC system is proposed and the system performances for processing handwritten numeral recognition (HNR) are analyzed. For such a system, a masked handwritten numeral information is injected into the first reservoir layer, the different value between two adjacent node states of the first reservoir layer is sent to the second reservoir layer, and the virtual node states of the second reservoir layer are extracted for training and testing. The simulated results show that, by optimizing the system parameters, a word error rate (WER) of 0.11 for processing HNR can be achieved. By comparing with an optoelectronic RC with a single reservoir layer, the optoelectronic RC with two reservoir layers possesses better performances for processing HNR.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.