Symmetric 10G-EPON ONU transceiver integrated with newly-developed burst-mode pre-bias timing control IC
We developed symmetric 10G-EPON ONU transceiver fully compliant with IEEE802.3av PR30. Output power of +5 dBm, sensitivity of -32.4 dBm, and fast LD turn-on/off time of 10 ns/7 ns were successfully achieved by newly-developed burst-mode pre-bias timing control IC.
Demonstration of 10G-EPON and GE-PON Coexisting System Employing Dual-Rate Burst-Mode 3R Transceiver
In this letter, a novel 10 gigabit Ethernet passive optical network (10G-EPON) optical line terminal (OLT) dual-rate burst-mode reshaping, retiming, and regenerating transceiver was, for the first time, reported to completely meet the IEEE802.3 av 10G-EPON standards where the coexisting of 10G-EPON and gigabit Ethernet passive optical network (GE-PON) systems on the same fiber plant is specified. Newly developed 10G/1G dual-rate burst-mode avalanche photodiode preamplifier and dual-rate 82.5-GS/s burst-mode clock and data recovery achieved the high receiver sensitivity and the wide burst dynamic range of -31.2 dBm/25.2 dB (at bit-error rate (BER) = 1 X 10-3) for 10.3 Gb/s and -35.6 dBm/26.3 dB (at BER = 1 x 10-12) for 1.25 Gb/s. Moreover, 10G-EPON and GE-PON coexisting system of 32 x optical network units with loss budget of 33.5 dB was successfully demonstrated.
Texture Feature Extraction of RGB, HSV, YIQ and Dithered Images using GLCM, Wavelet Decomposition Techniques
When changing the format of an image from simple RGB to HSV, YIQ and Dithered image, the characteristics of image also change. In this paper, the similar images in the above formats are retrieved using statistical and structural retrieving techniques i.e. GLCM (Gray Level Co-occurrence Matrix) and Wavelet Decomposition techniques. The best results are coming for dithered, HSV images by using GLCM technique for feature extraction and by using Wavelet decomposition; HSV images are giving the best results. While other formats also give the correct retrieval but from the accuracy point of view, HSV images are retrieved with better accuracy using both techniques.