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Atsushi A. YAMAGUCHI Kohei KAWAKAMI Naoto SHIMIZU Yuchi TAKAHASHI Genki KOBAYASHI Takashi NAKANO Shigeta SAKAI Yuya KANITANI Shigetaka TOMIYA
Internal quantum efficiency (IQE) is usually estimated from temperature dependence of photoluminescence (PL) intensity by assuming that the IQE at cryogenic temperature is unity. III-nitride samples, however, usually have large defect density, and the assumption is not necessarily valid. In 2016, we proposed a new method to estimate accurate IQE values by simultaneous PL and photo-acoustic (PA) measurements, and demonstratively evaluated the IQE values for various GaN samples. In this study, we have applied the method to InGaN quantum-well active layers and have estimated the IQE values and their excitation carrier-density dependence in the layers.
Hisashi AOMORI Kohei KAWAKAMI Tsuyoshi OTAKE Nobuaki TAKAHASHI Masayuki YAMAUCHI Mamoru TANAKA
The lifting scheme is an efficient and flexible method for the construction of linear and nonlinear wavelet transforms. In this paper, a novel lossless image coding technique based on the lifting scheme using discrete-time cellular neural networks (DT-CNNs) is proposed. In our proposed method, the image is interpolated by using the nonlinear interpolative dynamics of DT-CNN, and since the output function of DT-CNN works as a multi-level quantization function, our method composes the integer lifting scheme for lossless image coding. Moreover, the nonlinear interpolative dynamics by A-template is used effectively compared with conventional CNN image coding methods using only B-template. The experimental results show a better coding performance compared with the conventional lifting methods using linear filters.