REV Journal on Electronics and Communications
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230 research outputs found
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A Novel Joint Blocking and Ringing Artifact Reduction using Advanced Beltrami Based Texture Maps
No full textThis paper proposes a novel image enhancement approach using advanced texture maps together with isotropic or directional fuzzy filters. Texture maps of original images or compressed images are estimated and then are used to control the filter’s strength. The aim is to reduce blocking and ringing artifacts while preserving the sharpness of compressed images. The spread parameter of fuzzy filters plays an important role to control deblocking and deringing process. Thus, the spread parameter is optimized to obtain the highest image quality. The proposed algorithm also simultaneously combines deblocking and deringing schemes to reduce the algorithm’s complexity. Simulation results show that the proposed fuzzy filtering scheme achieves the best visual quality, SSIM, and PSNR values among existing methods
New Algorithm for Detecting Target on the Clutter Background Using Polarimetric Parameter
No full textThis paper proposes a new algorithm for detecting radar targets on the clutter background using a nonenergy polarimetry parameter, the ellipticity coefficient. The algorithm ultilises two-level threshold dectector (is used in this algorithm). Probability density function of ellipticity coefficient is calculated for two classes of target: target in clutter and only clutter. The optimum detection threshold is calculated based on the Neyman-Pearson criteria. In this paper, the detection threshold and the probability of detection are calculated based on a given false alarm, different signal to background clutter ratios, and with different polarimetric features of the background clutter. Proposed algorithm shows the efficiency of using ellipticity coefficient in detecting target on the background clutter
An Online Distributed Boundary Detection and Classification Algorithm for Mobile Sensor Networks
Get PDFWe present a novel online distributed boundary detection and classification algorithm in order to improve accuracy of boundary detection and classification for mobile sensor networks. This algorithm is developed by incorporating a boundary detection algorithm and our newly proposed boundary error correction algorithm. It is a fully distributed algorithm based on the geometric approach allowing to remove boundary errors without recursive process and global synchronization. Moreover, the algorithm allows mobile nodes to identify their states corresponding to their positions in network topologies, leading to self-classification of interior and exterior boundaries of network topologies. We have demonstrated effectiveness ofthis algorithm in both simulation and real-world experiments and proved that the accuracy of the ratio of correctly identified nodes over the total number of nodes is 100%
A Robust Mobile Robot Navigation System using Neuro-Fuzzy Kalman Filtering and Optimal Fusion of Behavior-based Fuzzy Controllers
Get PDFThis study proposes a control system model for mobile robots navigating in unknown environments. The proposed model includes a neuro-fuzzy Extended Kalman Filter for localization task and a behaviorbased fuzzy multi-controller navigation module. The neuro-fuzzy EKF, used for estimating the robot’s position from sensor readings, is an enhanced EKF whose noise covariance matrix is progressively adjusted by a fuzzy neural network. The navigation module features a series of independently-executed fuzzy controllers, each deals with a specific navigation sub-task, or behavior, and a multi-objective optimizer to coordinate all behaviors. The membership functions of all fuzzy controllers play the roles of objective functions for the optimizer, which produces an overall Pareto-optimal control signal to drive the robot. A number of simulations and real-world experiments were conducted to evaluate the performance of this model
A Multi-Criteria based Software Defined Networking System Architecture for DDoS-Attack Mitigation
Get PDFNowadays, Software-Defined Networking (SDN) has become a promising network architecture in which network devices are controlled in a separate Control Plane (i.e., SDN controller). In a specific aspect, employing SDN in a network offers an attractive network security solution due to its flexibility in building and adding more new software security rules. From another perspective, attack prediction and mitigation, especially for Distributed Denial of Service (DDoS) attacks, are still challenges in SDN environments since a SDN control system works probably slower than a non-SDN one and theSDN controller can become a target of attacks. In this article, at first, we analyze a real traffic use case in order to derive DDoS indicators and thresholds. Secondly, we design an Openflow/SDN-based Attack Mitigation Architecture that is able to quickly mitigate DDoS attacks on the fly. The design solves the existing problems of the Openflow protocol, reducing the traffic volume traversing over the interface between the data plane (switch) and the control plane (SDN controller) and decreasing the buffer size at the Openflow switch. Applying our proposed Fuzzy Logic-based DDoS Mitigation algorithm that deploys multiple criteria for DDoS detection - FDDoM, the system demonstrates the ability to detect and filter 97% of attack flows and reach a False Positive Rate of 5% that are acceptable figures in real system management. The results also show that the network resource which is required to cope and maintain flow entries is 50% reduced during attack time
Double-Side Electromagnetic Band Gap Structure for Improving Dual-Band MIMO Antenna Performance
Get PDFA double-side EBG structure with equivalent circuit model is proposed in this paper. Making H shape on surface and H with bridge shape on ground, the novel EBG that is built on FR4 substrate with height of 1.6mm, gets compact size of 8.6x8.6 mm2 at 2.6 GHz resonant frequency. Using 1x7 EBG structures for dual-band MIMO system, several performance parameters of antenna are improved. Firstly, the mutual coupling between antenna elements gets -40dB in the lower band and -30dB in the higher one with narrow distance of 0.11l from feeding point to feeding point. Then, at 2.6GHz, the antenna gain is increased significant by 160% as well as radiation efficiency of antenna is better. This improvement is unable to get in previous EBG studie
A Distributed Heuristic Algorithm for Delay Constrained Energy Efficient Routing in Wireless Sensor Networks
Get PDFBesides energy restriction, wireless sensor networks (WSNs) should be able to provide bounded end-to-end delay when they are used to support real-time applications such as early forest fire alarm systems. In this paper, we investigate the problem of finding the least energy consumption route subject to a delay constraint with low computational complexity in such networks. Based on the distance-vector routing approach, which has less computational complexity and message overhead, we propose a distributed heuristic algorithm called Delay Constrained Energy Efficient Routing (DCEER) in order to minimize the total energy consumption while meeting the end-to-end delay requirement. DCEER only requires a moderate amount of information at each sensor node and does not suffer from the excessive running time. We prove that our proposed algorithm always finishes within a finite time and the computation complexity is only O(n), where n is a divisor of the number of sensor nodes. By mathematical proof and simulation, we verify that DCEER is suitable for large-scale WSNs because the number of messages exchanged between sensor nodes are represented by a polynomial function. Furthermore, we evaluate our proposal to compare its performance with related protocols
New Adaptive Neural Network for Uncertain Nonlinear System with Disturbance
Get PDFAn output of RBF neural network depends linearly on the matrix weights, a training is thus a linear optimization problem. However, by adjusting the centers and the widths this type of neural network structure becomes nonlinearly parameterized. In this work, lumped disturbances consisting of both approximation errors and external disturbance are estimated by an adaptive RBF neural network structure combining with a feed-forward correction, in which the feed-forward correction term is calculated by the algebraic equation regarding the parameters of controller and the radial basis function. This estimator (using estimating the lumped disturbance) is also used both in class of SISO nonlinear and MIMO nonlinear system. In addition, an adaptive scheme for the RBF neural network (an output and n outputs) is developed to approximate unknown system functions. On the other side, the performance of closed loop system (settling time, overshoot and the static error) would be improved by using an adaptive law to update the parameters of controller instead of choosing fixed controller's parameters which are coefficients of hurwitz polynomial. Thanks to Lyapunov's theory, asymptotic stability is established with the tracking errors converging to a neighborhood of the origin. Finally, there are two examples, coupled tank liquid system and an active magnetic bearing system, are presented to illustrate the our proposed methods
Low Profile Frequency Reconfigurable PIFA Antenna using Defected Ground Structure
Get PDFIn this paper, we design and implement a low profile frequency reconfigurable Planar Inverted-F Antenna (PIFA) for WLAN, m-WiMAX and UMTS applications. Dierent from several conventional designs, the air layer in our antenna is removed, while the radiator patches and ground plane are printed on two sides of the same substrate. This makes the antenna structure thin and lightweight. The defected ground structure (DGS) and coplanar sorting-trips are also designed for adjusting lower operating frequencies without increasing the antenna’s size. Three PIN-diodes are used in appropriate positions for accurate switches between frequency bands. Moreover, the three radiator patches’ parameters are optimally selected on all configurations using Genetic Algorithm (GA). Simulation results show that depending on the ON/OFF states of the PIN-diodes, the antenna can operate in three applicable frequency bands, i.e., 2.1 GHz, 2.4 GHz, and 3.5 GHz with the corresponding peak gains of 0.48 dBi, 3.55 dBi, and 4.33 dBi. The antenna occupies an overall size of 63.5x33.5x1.6 mm3, which can be easily fabricated and integrated into small wireless devices. Simulated and measured results are also compared to validate the correctness the antenna design