Implementation of some signal processing algorithms on hardware has generally an advantage of efficiently implementation of complex processing. However, it still has some difficulties of developing natural optical phenomena because of various trade-off relation. Since these difficulties do not always allow a photonic hardware to emulate such an intermediary processing, further little assistances are necessary to complete the gap bridge and various machinelearning would play a significant role there. We discuss machine-learning-aided photonic hardware implementation incorporating natural optical phenomena with an example of a spectroscopic inspection technique for low cost, high speed, large data, and high spectral resolution.
We report optical Nyquist pulse train generation by non-auxiliary wavelength selective switch (WSS) in communication band. Nyquist pulses have the attractive feature of tolerance to inter-symbol interference (ISI), which means that densely arranged pulse trains are possible. The typical approach for optical Nyquist pulse train generation uses an auxiliary optical circuit for time division multiplexing as well as a WSS for a single Nyquist pulse generation. The auxiliary use of the optical circuit gives rise to optical losses and inflexibility of pulse-train parameters. The optical loss is estimated as 10 dB even if an ideal optical circuit is used in the case of 10-multiplexing. To resolve these problems, we have recently proposed a new approach for optical Nyquist pulse train generation by non-auxiliary WSS in the near-infrared band, where the WSS combines a single Nyquist pulse generation and time division multiplexing. The key point of the approach is how to design a filter function to minimize the optical loss. We have established the method to design the low-loss filter function, which takes advantage of the ISI-free property of Nyquist pulses. We have experimentally demonstrated Nyquist pulse train generation with the proposed approach in the near-infrared band. In this report, we widen its application range to the optical communication band, and experimental results show that the optical loss for 10- multiplexing is successfully reduced to 1.36 dB. The new approach without an auxiliary optical circuit realizes low-loss, highly flexible and compact optical Nyquist pulse train generator in the optical communication band.
Optical fiber sensor networks have attracted much attention in IoT technology and a fiber Bragg grating is one of key sensor devices there because of their advantages in a high affinity for optical fiber networks, compactness, immunity to electromagnetic interference and so on. Nevertheless, its sensitivity is not always satisfactory so as to be usable together with widespread cost-effective multi-channel spectrometers. In this paper, we introduce a new cost-effective approach for a portable multi-channel spectrometer with high spectral resolution and demonstrates some preliminary experimental results for fine FBG sensing.
We report an optical pulse profiling method which has a potential to enable real-time stamping of optical pulse waveforms to corresponding characteristic spectra without any user's expertise and skills. Its performance was confirmed by comparison with the conventional matured measurement tools and was as accurate as the conventional ones. The concept can be extended for real-time measurement of pulse-by-pulse phenomena provided the use of fast spectrum analyzers enables to acquire and storage pulse-by-pulse spectrum in real-time.
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