In the field of radiocommunication, modulation type identification is one of the most important characteristics in signal processing. This study aims to implement a modulation recognition system on two approaches to m...In the field of radiocommunication, modulation type identification is one of the most important characteristics in signal processing. This study aims to implement a modulation recognition system on two approaches to machine learning techniques, the K-Nearest Neighbors (KNN) and Artificial Neural Networks (ANN). From a statistical and spectral analysis of signals, nine key differentiation features are extracted and used as input vectors for each trained model. The feature extraction is performed by using the Hilbert transform, the forward and inverse Fourier transforms. The experiments with the AMC Master dataset classify ten (10) types of analog and digital modulations. AM_DSB_FC, AM_DSB_SC, AM_USB, AM_LSB, FM, MPSK, 2PSK, MASK, 2ASK, MQAM are put forward in this article. For the simulation of the chosen model, signals are polluted by the Additive White Gaussian Noise (AWGN). The simulation results show that the best identification rate is the MLP neuronal method with 90.5% of accuracy after 10 dB signal-to-noise ratio value, with a shift of more than 15% from the k-nearest neighbors’ algorithm.展开更多
The detection and characterization of human veins using infrared (IR) image processing have gained significant attention due to its potential applications in biometric identification, medical diagnostics, and vein-bas...The detection and characterization of human veins using infrared (IR) image processing have gained significant attention due to its potential applications in biometric identification, medical diagnostics, and vein-based authentication systems. This paper presents a low-cost approach for automatic detection and characterization of human veins from IR images. The proposed method uses image processing techniques including segmentation, feature extraction, and, pattern recognition algorithms. Initially, the IR images are preprocessed to enhance vein structures and reduce noise. Subsequently, a CLAHE algorithm is employed to extract vein regions based on their unique IR absorption properties. Features such as vein thickness, orientation, and branching patterns are extracted using mathematical morphology and directional filters. Finally, a classification framework is implemented to categorize veins and distinguish them from surrounding tissues or artifacts. A setup based on Raspberry Pi was used. Experimental results of IR images demonstrate the effectiveness and robustness of the proposed approach in accurately detecting and characterizing human. The developed system shows promising for integration into applications requiring reliable and secure identification based on vein patterns. Our work provides an effective and low-cost solution for nursing staff in low and middle-income countries to perform a safe and accurate venipuncture.展开更多
Abstract： This work proposes a Field Programmable Gate Array （FPGA）-oriented architecture for the IEEE 802.11 Distributed Coordination Function （DCF） transceiver. We describe the functional blocks carrying out th...Abstract： This work proposes a Field Programmable Gate Array （FPGA）-oriented architecture for the IEEE 802.11 Distributed Coordination Function （DCF） transceiver. We describe the functional blocks carrying out the Carrier Sense Multiple Accesses with Collision Avoidance （CSMA/CA）, develop the interfaces to the application layer and the physical layer, and implement it on FPGA devices by utilizing Very-high-speed-integrated-circuit Hardware Description Language （VHDL）.展开更多
When attempting to understand where domestic plants and animals were domesticated, it is essential to consider the geographic distribution of the wild ancestor. Many domestic taxa now inhabit just about every continen...When attempting to understand where domestic plants and animals were domesticated, it is essential to consider the geographic distribution of the wild ancestor. Many domestic taxa now inhabit just about every continent thanks to their human-mediated dispersal which began soon after they were incorporated into the human niche.展开更多
A new concept, the generalized inverse group (GIG) of signal, is firstly proposed and its properties, leaking coefficients and implementation with neural networks are presented. Theoretical analysis and computational ...A new concept, the generalized inverse group (GIG) of signal, is firstly proposed and its properties, leaking coefficients and implementation with neural networks are presented. Theoretical analysis and computational simulation have shown that (1) there is a group of finite length of generalized inverse signals for any given finite signal, which forms the GIG; (2) each inverse group has different leaking coefficients, thus different abnormal states; (3) each GIG can be implemented by a grouped and improved single-layer perceptron which appears with fast convergence. When used in deconvolution, the proposed GIG can form a new parallel finite length of filtering deconvolution method. On off-line processing, the computational time is reduced to O(N) from O(N2). And the less the leaking coefficient is, the more reliable the deconvolution will be.展开更多
This paper proposes two migration scenarios from China ring networks to ASON mesh networks. In our quantitative analysis with ASON/GMPLS simulator, a subnetwork protection scheme achieved best balanced performance in ...This paper proposes two migration scenarios from China ring networks to ASON mesh networks. In our quantitative analysis with ASON/GMPLS simulator, a subnetwork protection scheme achieved best balanced performance in resource utilization and restoration time.展开更多
We propose a technique for chromatic dispersion monitoring based on optical time domain level monitoring. Experimental and simulation results show that the technique is effective for the monitoring of dispersion in 42...We propose a technique for chromatic dispersion monitoring based on optical time domain level monitoring. Experimental and simulation results show that the technique is effective for the monitoring of dispersion in 42.7-Gbps CS-RZ signals for dynamic dispersion compensation.展开更多
We report on the effects of the polarization-dependent loss (PDL) on the polarization-multiplexed system. The result shows that the PDL of 0.9 dB could cause 1-dB power penalty. Unlike PMD, the effect of PDL was not d...We report on the effects of the polarization-dependent loss (PDL) on the polarization-multiplexed system. The result shows that the PDL of 0.9 dB could cause 1-dB power penalty. Unlike PMD, the effect of PDL was not dependent on the transmission speed.展开更多
文摘In the field of radiocommunication, modulation type identification is one of the most important characteristics in signal processing. This study aims to implement a modulation recognition system on two approaches to machine learning techniques, the K-Nearest Neighbors (KNN) and Artificial Neural Networks (ANN). From a statistical and spectral analysis of signals, nine key differentiation features are extracted and used as input vectors for each trained model. The feature extraction is performed by using the Hilbert transform, the forward and inverse Fourier transforms. The experiments with the AMC Master dataset classify ten (10) types of analog and digital modulations. AM_DSB_FC, AM_DSB_SC, AM_USB, AM_LSB, FM, MPSK, 2PSK, MASK, 2ASK, MQAM are put forward in this article. For the simulation of the chosen model, signals are polluted by the Additive White Gaussian Noise (AWGN). The simulation results show that the best identification rate is the MLP neuronal method with 90.5% of accuracy after 10 dB signal-to-noise ratio value, with a shift of more than 15% from the k-nearest neighbors’ algorithm.
文摘The detection and characterization of human veins using infrared (IR) image processing have gained significant attention due to its potential applications in biometric identification, medical diagnostics, and vein-based authentication systems. This paper presents a low-cost approach for automatic detection and characterization of human veins from IR images. The proposed method uses image processing techniques including segmentation, feature extraction, and, pattern recognition algorithms. Initially, the IR images are preprocessed to enhance vein structures and reduce noise. Subsequently, a CLAHE algorithm is employed to extract vein regions based on their unique IR absorption properties. Features such as vein thickness, orientation, and branching patterns are extracted using mathematical morphology and directional filters. Finally, a classification framework is implemented to categorize veins and distinguish them from surrounding tissues or artifacts. A setup based on Raspberry Pi was used. Experimental results of IR images demonstrate the effectiveness and robustness of the proposed approach in accurately detecting and characterizing human. The developed system shows promising for integration into applications requiring reliable and secure identification based on vein patterns. Our work provides an effective and low-cost solution for nursing staff in low and middle-income countries to perform a safe and accurate venipuncture.
基金the National Natural Science Foundation of China
文摘Abstract： This work proposes a Field Programmable Gate Array （FPGA）-oriented architecture for the IEEE 802.11 Distributed Coordination Function （DCF） transceiver. We describe the functional blocks carrying out the Carrier Sense Multiple Accesses with Collision Avoidance （CSMA/CA）, develop the interfaces to the application layer and the physical layer, and implement it on FPGA devices by utilizing Very-high-speed-integrated-circuit Hardware Description Language （VHDL）.
文摘When attempting to understand where domestic plants and animals were domesticated, it is essential to consider the geographic distribution of the wild ancestor. Many domestic taxa now inhabit just about every continent thanks to their human-mediated dispersal which began soon after they were incorporated into the human niche.
基金Supported partly by Natural Science Foundation of ChinaAviation Science Grant of China
文摘A new concept, the generalized inverse group (GIG) of signal, is firstly proposed and its properties, leaking coefficients and implementation with neural networks are presented. Theoretical analysis and computational simulation have shown that (1) there is a group of finite length of generalized inverse signals for any given finite signal, which forms the GIG; (2) each inverse group has different leaking coefficients, thus different abnormal states; (3) each GIG can be implemented by a grouped and improved single-layer perceptron which appears with fast convergence. When used in deconvolution, the proposed GIG can form a new parallel finite length of filtering deconvolution method. On off-line processing, the computational time is reduced to O(N) from O(N2). And the less the leaking coefficient is, the more reliable the deconvolution will be.
文摘This paper proposes two migration scenarios from China ring networks to ASON mesh networks. In our quantitative analysis with ASON/GMPLS simulator, a subnetwork protection scheme achieved best balanced performance in resource utilization and restoration time.
文摘We propose a technique for chromatic dispersion monitoring based on optical time domain level monitoring. Experimental and simulation results show that the technique is effective for the monitoring of dispersion in 42.7-Gbps CS-RZ signals for dynamic dispersion compensation.
文摘We report on the effects of the polarization-dependent loss (PDL) on the polarization-multiplexed system. The result shows that the PDL of 0.9 dB could cause 1-dB power penalty. Unlike PMD, the effect of PDL was not dependent on the transmission speed.
