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Abstract— In OFDM systems, it is necessary to estimate the channel to overcome the distortion caused by channel fading’s which can be induced by many phenomena such as: delay spread, mobility and Doppler shift. Most of the channel estimation techniques are proposed in frequency domain using the pilot symbols. One of them that is less complicated is least-squares (LS) method which is widely used in channel estimation but it is more sensitive to noise respected to the other reported techniques. In this paper, a new threshold based method using wavelet decomposition will be proposed which is based on an initial LS estimation technique. The reported simulation results show that the proposed method has better performance compared to the other methods such as Lee Method that has been published recently.

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In this paper, a new approach for controller designing of robust output feedback model reference adaptive control with a function of tracking error for a class of continuous linear systems with multiple uncertain time varying state delays is introduced. Proposed controller is not only robust versus of multiple uncertain time delays and external disturbance with uncertain bound but also improve performance of transient and steady state of closed loop system. The stability of closed loop system and error convergence is shown with an appropriate Lyapunov-Krasovskii function. Simulation results show good performance of proposed controller.

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Blind source separation is the technique that anyone can separate the original signals from their mixtures without any knowledge about the mixing process, but using some statistical properties of original source signals. Independent component analysis is a statistical method expressed as a set of multidimensional observations that are combinations of unknown variables which are assumed to be statistically independent with respect to each other. In this paper we will use the nonlinear autcorrelation function as an object function to separate the source signals from the noisy mixing signals. Also we apply the wavelet transform in our proposed algorithm. Maximization of the object function in wavelet domain using the LMS algorithm will be obtained the coefficients of a linear filter which separate the source signals with high SNR. To calculate the performance of the proposed algorithm, two parameters of Performance Index and Signal to Noise and Interference Ratio will be used. To test the proposed algorithm, we will use Inovation Gaussian signals, Speech signals and ECG signals. Finally level of wavelet decomposition effects will be consider on the obtained results. It will be shown that the proposed algorithm gives better results than the other methods such as NoisyNA method that has been proposed by Shi.

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Generally nonlinear modelling of aerospace system has uncertainty in model parameters and also in real situation different disturbances are applied to system. In spite of these uncertainties and disturbances, autopilot control system should be guarantee stability and desired performance of system. The conditions such as fast response, low tracking error, system robustness must be considered in autopilot design. In this paper, a new method is suggested to reduce the tracking error and increase system robustness. The proposed method is based on Backstepping approach. To reduce the tracking error, resulted from the simplification of the missile model, a nonlinear disturbance observer is used to estimate the uncertainty and also update the reference signal. In addition nonlinear disturbance observer is used to eliminate output disturbance. The advantage of the proposed method is its complete flexibility and also it can be employ for linear and nonlinear systems

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Epilepsy is the most common serious brain disorder that characterized by recurrent seizures. Epilepsy affects 65 million people worldwide today and about two million new cases occur each year. The most negative aspect of seizure that causes the patient couldn’t have normal life, is its sudden and incontrollable features. So, the achievement of an algorithm that is capable to predicting the occurrence of seizures would help sufferers to live a normal life safe, and they can move out of harm's way. In this study, we proposed a prediction method for absence seizures based on the time-frequency analysis and complexity measure in EEG signals of WAG/Rij rats as a valid animal model of human absence epilepsy. We investigated the changes of permutation Entropy and the wavelet power of theta frequency range, simultaneously. The proposed seizures prediction algorithm was applied to long-term EEG recordings of WAG/Rij rats. The results indicate that the algorithm successfully detected the pre-ictal state prior to onset of seizures in 210 out of 298 seizures.The dependence of accuracy, sensitivity and anticipation time of prediction algorithm on program settings and attributes of EEG recordings are discussed.In this study, we found that the measure of PE reduced in pre-ictal and ictal states of EEG signals in these rats. The reduction of complexity of EEG signals prior to onset of seizures that was demonstrated by means of PE might be indicating the neural synchronization of brain networks in WAG/Rij rats.

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In this paper, we investigate the design method for interval type-2 (IT2) T-S fuzzy controller based on IT2 T-S fuzzy observer for nonlinear systems along with uncertainty parameters. In order to analyze the stability and synthesis the control methods conveniently, an IT2 (T–S) fuzzy model is applied through representing the dynamic of nonlinear systems and dynamic of observer. Uncertainty parameters are captured by IT2 membership function characterized by the lower and upper membership functions. In this paper, for IT2 fuzzy controller, the membership functions and number of rules can be freely chosen different from the IT2 T–S fuzzy model and IT2 T-S fuzzy observer. This method is known non- Parallel Distributed Compensation. To reduce the conservativeness of stability analysis, a fuzzy Lyapunov function candidate is applied. The stability conditions in term of linear matrix inequlities (LMIs) are obtained.

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In recent years, simultaneous localization and mapping (SLAM) has become a very challenging matter as a basic problem in the mobile robots navigation. This paper describes a new efficient inertial SLAM algorithm for a UAV or an airborne. This inertialSLAM could be properly applied to two different kinds of sensors: (i)Range/Bearing sensorsand (ii)Bearing-only sensors and so it does not need to any other external positioning systems like as GPS or any preprovided data. In this study, acomprehensive system has been presented which not only enhances the three-dimensional SLAM accuracy and performance, but overcomes the two fundamental problems that have less been noticed in previous researchesA) To consider all the degrees of freedom for the UAV that lets the UAV height changesbe usedin addition to two x and y directions. B) It does not experience any limit for the symbols status which means that the system is able to observe all the symbolsin different heights based on inertia sensors. Finally, the accuracy of proposed algorithm has been approved due to the simulation results using the actual aircraft flight data.

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In this paper joint effect of transmitter and receiver IQ imbalance under insufficient and sufficient cyclic prefix (CP) is studied. The case of insufficient CP length leads to increase in the rate of symbol transmission, on the other hand it causes inter-symbol-interference. Morever, existence of IQ imbalance in the transmitter and receiver causes distortion in the received signals. So this problem leads to increase of bit error rate. To compensation of this effect and other impairments, simultaneously, per-tone equalization (PTEQ) structure implementation is necessary. Regarding to topology of this structure and required high length filters, the system computations will be very high, even using simplest adaptive algorithms. In this work to reduce the computational burden, an adaptive algorithm based on selective coefficient updating (SCU) has been presented. In addition, to increase of the convergence speed of adaptive algorithms,wavelet packet transform (WPT) is applied to branches of PTEQ structure in second stage. Then SCU method based on the rate of wavelet papcket entropy has been used. It must be mentioned that in this method not only computational complexity has been reduced but also bit error rate has been improved. In the third stage, the combination of both SCU and data selective updating (DSU) to increase of convergence speed and to reduce of computational complexity have been derived. Simultaneous using of two DSU and SCU methods besides WPT, is suitable for compensation ofchannel effect and IQ imbalance. Simulation results show that this algorithm not only causes considerably reduction on amount of calculations, but also have better performance.

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A novel current source multilevel inverter is introduced in this paper which is an appropriate alternative to be employed for low/medium power applications. the proposed converter is formed basic modules which paralleling these modules increse output current levels and improve quality of injected current to load or grid. in order to validate advantages of proposed converter versus the several multilevel current source inverters, a full comparison is provided. the simulation results shows the good performance of the proposed converter in off grid and grid-connected applications. Also experimental results for single-phase load confirm the practicablity of the proposed converter.

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This paper evaluates the problem of user pairing scenario with similar channel conditions in NOMA with three users per pair. The small difference in the channel gain of the paired users leads to interference in the process of successive interference cancelation (SIC). The incidence of imperfect SIC reduces system capacity. Also, mid users in this scenario will be deprived of the advantages provided by the NOMA without pairing, on the other hand, by pairing,  due to the closeness of the users’ channel conditions to each other, leads to the incidence of imperfect SIC. In this paper, in order to solve this problem, we propose a scenario for users to pair, in which all users, including mid users, will be able to use the benefits of NOMA and the problem of incidence of imperfect SIC is minimized. To evaluate the performance of the NOMA, we examine the sum ergodic capacity in both perfect and imperfect SIC modes. In this paper, the concept of an imperfect SIC has calculated analytically for the first time for pairs containing three users. The calculations performed along with the simulations show that in this case, the system's capacity falls sharply. The simulation results also show that the proposed scenario, in addition to minimizing the imperfect SIC event, provides a higher sum ergodic capacity than other scenarios.

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This paper presents a new circuit to configure power amplifier (PA) for return-to-zero on-off-keying (RZ-OOK) transmitters. The proposed PA works as a multimode structure with configurable data rate and output power. The programmable data rate function is achieved by duty cycle adjustment of input data and producing input RZ-data by a simple circuit, which leads to a linear scale of data rate with power consumption. This implies that any desired level of output power can be transmitted with different power consumption according to the power budget. The RZ-data is also utilized to perform the output power reconfiguration. The PA represents data rate of 0.3Mb/s to 3Mb/s and it can deliver output power level from -23dBm to 0dBm. During data rate adjustment, power consumption varies from 0.099mW to 0.99mW when the output power is 0dBm. Also, PA consumes 0.07mW to 0.99mW at the output power tuning range with a data rate of 3Mb/s.