ELECTRONIC INDUSTRIES
Year:2015 | Volume:6 | Issue:2|Papers Count:8

Hyperspectral images clustering, for the appropriate number of clusters, due to their high volume and high noise level is a difficult matter. The proposed method in this paper is a composition of fuzzy clustering algorithms that offers the optimal number of clusters along with the clustered image. The method is based on a hierarchical approach and acts using three fuzzy algorithms FCM, weighted G-K and MCV. Hence, the different shapes of clusters are identified and the sum volume of every cluster is minimum. Each of the clusters according to the proposed condition are separated as step to step, until the appropriate number of clusters are obtained. After implementing the proposed approach on two different hyperspectral images and use of cluster validity parameters, more appropriate values of these parameters is obtained for this method than other fuzzy methods. Finally, a good clustering can be obtained by determining the number of clusters. The results of the cluster assessment such as partition coefficient show that the proposed method, less scattered examples is presented in the clustered image, on the other hand, similarity the samples in each cluster is considerable than other methods.

Reaction thrusters using in spacecrafts attitude control will be highly regarded, because they can provide almost any torque level, despite complexity analysis. Also suitable control of satellite with thrusters depends on efficient and desired arrangement of thrusters on satellite body. Two important subject of arrangement design are fuel efficiency and increase reliability. System needs a large number of fixed thrusters to generate different torque level about three principal body axes and increase reliability, but this approach has not fuel efficiency. This problem is soluble with using gimbal thrusters. In gimbal thruster approach, by using two axis rotational elements, all of the workspace about three axes is covered with 2, 3 or 4 thrusters. In this paper after gimbal thrusters determination and structure description, their benefits than fixed thrusters is described. Then, different gimbal thrusters arrangement are designed and their workspace covering being analysis. Finally, desired arrangement with the best workspace covering and suitable reliability is selected for three axis attitude control.

Development of Internet network allows voice communication by Voice over Internet Protocol (VOIP). Session Initiation Protocol (SIP) is the most important signaling protocols in this network. This paper related to Denial of Service (DOS) attacks; specifically INVITE flooding attacks on SIP protocol. In this kind of attacks, an attacker disrupts Server network service by sending successive invite packets. In this paper, we explored modes of emergence INVITE flooding attack and the effects of this attack on SIP server. Results of this experiment indicate that after increasing attack rate, server CPU usage consumption surges. In addition, high CPU utilization leads to rise in the number of transmitted duplicate packets and reduced successful session. Moreover, we demonstrated that faster attack detection can be obtained by replacing Jeffrey distance instead of Hellinger distance.

In this article, a just-in-time adaptive distance metric learning for application in nonstationary environments is addressed. This generative model enables adaptive similarity-based classifiers to classify the time-labeled inquiry patterns which are coming from a nonparametric stochastic process with superior performance. Here, the performance points to accurately classification in low-dimensional feature space with minimum model adaptation during the system life time. While there are adaptive forms of feature extraction methods, which transform training patterns to a low-dimensional space and/or improve classifier accuracy, they are vulnerable to nonparametric changes in data and must continuously update their parameters. In the proposed method, an optimal transformation matrix transforms time-labeled instances from the original space to a new feature space to maximize the probability of selecting the correct class label for incoming instances using similarity-based classifiers. To this end, for a given time-labeled instance, nonparametric intra-class and extra-class distributions are proposed. The proposed method is also furnished to a temporal detector to provide the most convenient time for the adaptation phase. Experimental results on real and synthesized datasets that include real and artificial changes demonstrate the performance of the proposed method in terms of accuracy and dimension reduction in dynamic environments.

In this paper, the Nonlinear Model Predictive Control (NMPC) approach is employed to control the five-DOF biped robot in moving up and down the stairs. In the proposed method, the path planning is performed in real time. That is, there are no predefined trajectories to track by the robot and the motion of the robot is expressed in terms of some constraints. The main feature of the proposed method is the online path planning, which leads to more robustness of the controller against the uncertainties in the environment. Moreover, the NMPC is designed in such a way the robot is able to climb the stairs with different heights and depths; hence, the gaits are defined adaptively. One major issue in using the MPC is its dependency to an accurate model. In this paper, the robot is modeled online using the Radial Basis Function (RBF) neural networks. In this way, the NMPC is turned into an adaptive controller that can adapt itself to changes in the system parameters. Simulation results show good performance of the proposed method as compared to the recently proposed methods in literature.

This paper presents envelope shaping and linearization techniques for envelope-elimination-and-restoration (EER) power amplifiers in wideband applications. Although the EER technique can enhance the efficiency of the power amplifier, its use in the OFDM-based systems with stringent mask and EVM requirements needs additional considerations, especially for wideband signals. To satisfy the required spectral mask and EVM of the transmitter, two digital pre-distortion algorithms are implemented and compared for linearization of the EER system. To increase the output power and efficiency, envelope clipping technique is proposed for the EER transmitter. The imposed nonlinearity caused by the clipping can be reduced by the pre-distortion. Further, time delay mismatch between amplitude and phase paths is investigated and a solution is proposed for its alleviation. For accurate and realistic results, these techniques are tested under interlock operation of digital, analog, and RF segments of the EER system for 802.16e WiMAX signal. The co-simulation results show that the proposed techniques can enhance the efficiency and output power while satisfying the required linearity of the transmitter.

The beam forming algorithm presented in this paper is to achieve three simultaneous capability in a LEO satellite phase area antenna which are shaping the coverage area, beam steering and null steering. Shaping the coverage area is to adapt it with Iran geographical boundaries. Beam steering is done according to the satellite real time position that cause fix area coverage when the satellite is passing over the country. The pattern deep nulls are generated and directed such that cause deactivating deception receivers located out of the coverage area. The algorithm is based on Weighted Least Mean Square (WLMS) method and during its process the optimum phase and amplitude weights obtained to excite array antenna elements. Simulation results shows that a 10*10 array using above algorithm can make a coverage with arbitrary shape, steer its beam in the range of -40o £ q £ +40o and 0o £ j £ 360o, fix the coverage on the intended area and deactivate deception receivers.

Self-adaptive software systems by eliminating human intervention and replacing closed loop structures for opened loop ones, are able to adapt to runtime changes in the context. In this regard, a three-stage process consisting of detecting, decision-making and implementation is a suitable mechanism. Despite the importance of the decision stage on the appropriate implementation of a self-adaptive software system and given models for decision making, yet the development of self-adaptive systems is associated with challenges, and these models cannot have the full protection of the current environment Therefore, in this study, we propose a model based on the concepts related to the goal-based ways to support decision-making in self-adaptive systems. This model not only results in flexibility increase, but also covers some challenges facing self-adaptive systems. A case study is used in order to assess the proposed model, and the assessment results in the reduction of decision making time and increase of workload.