A 10 Gbit/s burst-mode preamplifier is designed for passive optical networks （PONs）. To achieve a high dynamic range and fast response, the circuit is DC coupled, and a feed-back type peak detector is designed to pe...A 10 Gbit/s burst-mode preamplifier is designed for passive optical networks （PONs）. To achieve a high dynamic range and fast response, the circuit is DC coupled, and a feed-back type peak detector is designed to perform auto-gaincontrol and threshold extraction. Regulated cascade （RGC） architecture is exploited as the input stage to reduce the input impedance of the circuit and isolate the large parasitic capacitance including the photodiode capacitance from the determination pole, thus increasing the bandwidth. This preamplifier is implemented using the low-cost 0. 13 ixm CMOS technology. The die area is 425 μm × 475 μm and the total power dissipation is 23.4 mW. The test results indicate that the preamplifier can work at a speed from 1.25 to 10.312 5 Gbit/s, providing a high transimpedance gain of 64.0 dBΩ and a low gain of 54. 6 dBl2 with a dynamic input range of over 22.9 dB. The equivalent input noise current is 23. 4 pA/ Hz1/2. The proposed burst amplifier satisfies related specifications defined in 10G-EPON and XG-PON standards.展开更多
One of the methods for biometric identification is facial features detection, and eye is an important facial feature in the face. In the recent years, automatically detecting eye with different image conditions is att...One of the methods for biometric identification is facial features detection, and eye is an important facial feature in the face. In the recent years, automatically detecting eye with different image conditions is attended. This paper proposes a method which can automatically detect eye in extensive range of images with different conditions. In the proposed method, first an image is enhanced by morphological operations then region of face is detected by hybrid projection function. To identify window of eye, vertical edge dominance map is used. The authors＇ method uses elliptical mask on eye image to detect center of pupil. The mask scans eye image to find minimum gray level because pupil is darkest part in eye image compared with 3 well-known methods. The accuracy of 99.53% on this This method has implemented on JAFFE face database and database confirms efficiency of the proposed method.展开更多
基金The Key Technology Research and Development Program of Jiangsu Province ( No. BE2008128)
文摘A 10 Gbit/s burst-mode preamplifier is designed for passive optical networks （PONs）. To achieve a high dynamic range and fast response, the circuit is DC coupled, and a feed-back type peak detector is designed to perform auto-gaincontrol and threshold extraction. Regulated cascade （RGC） architecture is exploited as the input stage to reduce the input impedance of the circuit and isolate the large parasitic capacitance including the photodiode capacitance from the determination pole, thus increasing the bandwidth. This preamplifier is implemented using the low-cost 0. 13 ixm CMOS technology. The die area is 425 μm × 475 μm and the total power dissipation is 23.4 mW. The test results indicate that the preamplifier can work at a speed from 1.25 to 10.312 5 Gbit/s, providing a high transimpedance gain of 64.0 dBΩ and a low gain of 54. 6 dBl2 with a dynamic input range of over 22.9 dB. The equivalent input noise current is 23. 4 pA/ Hz1/2. The proposed burst amplifier satisfies related specifications defined in 10G-EPON and XG-PON standards.
文摘One of the methods for biometric identification is facial features detection, and eye is an important facial feature in the face. In the recent years, automatically detecting eye with different image conditions is attended. This paper proposes a method which can automatically detect eye in extensive range of images with different conditions. In the proposed method, first an image is enhanced by morphological operations then region of face is detected by hybrid projection function. To identify window of eye, vertical edge dominance map is used. The authors＇ method uses elliptical mask on eye image to detect center of pupil. The mask scans eye image to find minimum gray level because pupil is darkest part in eye image compared with 3 well-known methods. The accuracy of 99.53% on this This method has implemented on JAFFE face database and database confirms efficiency of the proposed method.
