Iranian Journal of Electrical and Electronic Engineering

---

In an environment such as underwater channel where placing test equipments are difficult to handle, it is much practical to have hardware simulators to examine suitably designed transceivers (transmitter/receiver). The simulators of this kind will then allow researchers to observe their intentions and carry out repetitive tests to find suitable digital coding/decoding algorithms. In this paper, a simplified shallow water digital data transmission system is first introduced. The transmission channel considered here is a stochastic DSP hardware model in which signal degradations leads to a severe distortion in phase and amplitude (fades) across the bandwidth of the received signal. A computer base-band channel model with frequency non-selective feature is derived by the authors [10-11]. This system was based on fullraised cosine channel modelling and proved to be the most suitable for vertical and shortrange underwater communication csdfher), with a reflected path (specula component, when the acoustic hydrophone receives reflected signals from surface and bottom of the sea) and a random path (diffused component, when the acoustic hydrophone receives scattered signals from the volume of the sea). The model assumed perfect transmitter-receiver synchronization but utilized realistic channel time delays, and demonstrated the timevarying characteristics of an underwater acoustic channel observed in practice. In this paper, they are used to provide a full system simulation in order to design an adaptive receiver employing the most advanced digital signal processing techniques in hardware to predict realizable error performances.

---

This paper presents a parametric low differential order model, suitable for mathematically analysis for Induction Machines with faulty stator. An adaptive Kalman filter is proposed for recursively estimating the states and parameters of continuous–time model with discrete measurements for fault detection ends. Typical motor faults as interturn short circuit and increased winding resistance are taken into account. The models are validated against winding function induction motor modeling which is well known in machine modeling field. The validation shows very good agreement between proposed method simulations and winding function method, for short-turn stator fault detection.

---

A low complexity dynamic subcarrier and power allocation methodology for downlink communication in an OFDM-based multiuser environment is developed. The problem of maximizing overall capacity with constraints on total power consumption, bit error rate and data rate proportionality among users requiring different QOS specifications is formulated. Assuming perfect knowledge of the instantaneous channel gains for all users, a new simple algorithm is developed to solve the mentioned problem. We compare the sum capacity, proportionality, and computational complexity of the proposed algorithm with the one presented by Wong et al. Numerical results demonstrate that the proposed algorithm offers a performance comparable with Wong’s algorithm, yet complexity remains low and proportionality constraint will be tightly satisfied. As well, the proposed algorithm can provide a flexible trade-off between complexity, capacity and proportionality constraint.

---

This paper presents an algorithm for adaptive determination of the dead time

during transient arcing faults and blocking automatic reclosing during permanent faults on

overhead transmission lines. The discrimination between transient and permanent faults is

made by the zero sequence voltage measured at the relay point. If the fault is recognised as

an arcing one, then the third harmonic of the zero sequence voltage is used to evaluate the

extinction time of the secondary arc and to initiate reclosing signal. The significant

advantage of this algorithm is that it uses an adaptive threshold level and therefore its

performance is independent of fault location, line parameters and the system operating

conditions. The proposed algorithm has been successfully tested under a variety of fault

locations and load angles on a 400KV overhead line using Electro-Magnetic Transient

Program (EMTP). The test results validate the algorithm ability in determining the

secondary arc extinction time during transient faults as well as blocking unsuccessful

automatic reclosing during permanent faults.

---

An adaptive online flux-linkage estimation method for the sensorless control of switched reluctance motor (SRM) drive is presented in this paper. Sensorless operation is achieved through a binary observer based algorithm. In order to avoid using the look up tables of motor characteristics, which makes the system, depends on motor parameters, an adaptive identification algorithm is used to estimate of the nonlinear flux-linkage parameters. This method makes position and speed estimation more accurate and robust towards any model uncertainty, also it is suitable replacement for a priori knowledge of motor characteristics.

---

In this paper we present a general formalism for the establishment of the family of selective partial update affine projection algorithms (SPU-APA). The SPU-APA, the SPU regularized APA (SPU-R-APA), the SPU partial rank algorithm (SPU-PRA), the SPU binormalized data reusing least mean squares (SPU-BNDR-LMS), and the SPU normalized LMS with orthogonal correction factors (SPU-NLMS-OCF) algorithms are established by this general formalism. In these algorithms, the filter coefficients are partially updated rather than the entire filter coefficients at every iteration which is computationally efficient. Following this, the transient and steady-state performance analysis of this family of adaptive filter algorithms are studied. This analysis is based on energy conservation arguments and does not need to assume a Gaussian or white distribution for the regressors. We demonstrate the performance of the presented algorithms through simulations in system identification and acoustic echo cancellation scenarios. The good agreement between theoretically predicted and actually observed performances is also demonstrated

---

The aim of this study is to address a new feature extraction method in the area of the heart arrhythmia classification based on a metric with simple mathematical calculation called Curve-Length Method (CLM). In the presented method, curve length of the under study excerpted segment of signal is considered as an informative feature in which the effect of important geometric parameters of the original signal can be found. To show merits of the presented method, first the original electrocardiogram (ECG) in lead I is pre-processed by removing its baseline wander then by scaling it in the [-1,1] interval. In the next step, using a trous method, discrete wavelet scales 23 and 24 and smoothing function scale 22 are extracted. Afterwards, segments including samples of the QRS complex, P and T waves are estimated via an approximation criterion and CLM is implemented to extract corresponding features from aforementioned scales, smoothing function and also from each original segment. The resulted feature vector (including 12 components) is used to tune an Adaptive Network Fuzzy Inference System (ANFIS) classifier. The presented strategy is applied to classify four categories found in the MIT-BIH Arrhythmia Database namely as Atrial Premature Beat (APB), Left Bundle Branch Block (LBBB), Right Bundle Branch Block (RBBB) and Premature Ventricular Contraction (PVC) and average values of Se = 99.81%, P+ = 99.80%, Sp = 99.81% and Acc = 99.72% are obtained for sensitivity, positive predictivity, specifity and accuracy respectively showing marginal improvement of the heart arrhythmia classification performance.

---

When a detector sensitive to the target plume IR seeker is used for tracking airborne targets, the seeker tends to follow the target hot point which is a point farther away from the target exhaust and its fuselage. In order to increase the missile effectiveness, it is necessary to modify the guidance law by adding a lead bias command. The resulting guidance is known as target adaptive guidance (TAG). First, the pure proportional navigation guidance (PPNG) in 3-dimensional state is explained in a new point of view. The main idea is based on the distinction between angular rate vector and rotation vector conceptions. The current innovation is based on selection of line of sight (LOS) coordinates. A comparison between two available choices for LOS coordinates system is proposed. An improvement is made by adding two additional terms. First term includes a cross range compensator which is used to provide and enhance path observability, and obtain convergent estimates of state variables. The second term is new concept lead bias term, which has been calculated by assuming an equivalent acceleration along the target longitudinal axis. Simulation results indicate that the lead bias term properly provides terminal conditions for accurate target interception.

---

In this paper, we propose smart step closed-loop power control (SSPC) algorithm and base station assignment based on minimizing the transmitter power (BSAMTP) technique in a direct sequence-code division multiple access (DS-CDMA) receiver in the presence of frequency-selective Rayleigh fading. This receiver consists of three stages. In the first stage, with conjugate gradient (CG) adaptive beamforming algorithm, the desired users’ signal in an arbitrary path is passed and the inter-path interference is canceled in other paths in each RAKE finger. Also in this stage, the multiple access interference (MAI) from other users is reduced. Thus, the matched filter (MF) can be used for the MAI reduction in each RAKE finger in the second stage. Also in the third stage, the output signals from the matched filters are combined according to the conventional maximal ratio combining (MRC) principle and then are fed into the decision circuit of the desired user. The simulation results indicate that the SSPC algorithm and the BSA-MTP technique can significantly improve the network bit error rate (BER) in comparison with other algorithms. Also, we observe that significant savings in total transmit power (TTP) are possible with our proposed methods.

---

In order to detect targets upon sea surface or near it, marine radars should be capable of distinguishing signals of target reflections from the sea clutter. Our proposed method in this paper relates to detection of dissimilar marine targets in an inhomogeneous environment with clutter and non-stationary noises, and is based on adaptive thresholding determination methods. The variance and the mean values of the noise level have been estimated in this paper, based on non-stationary, statistical methods and thresholding has been carried out using the suggested two-pole recursive filter. Making the rate of false alarm constant, the concerned threshold resolves the hypothesis of existence or absence of the target signal. Performance of the mentioned algorithm has been compared with the well-known conventional method as CA-CFAR in terms of decreasing the losses and increasing calculation speed. The algorithm provided for detection of signal has been implemented as a part of signal-processing algorithms of some practical marine radar. The results obtained from the algorithm performance in a real environment indicate appropriate workability of this method in heterogeneous environment and non-stationary interference.

---

The paper addresses a new QRS complex geometrical feature extraction technique as well as its application for electrocardiogram (ECG) supervised hybrid (fusion) beat-type classification. To this end, after detection and delineation of the major events of ECG signal via a robust algorithm, each QRS region and also its corresponding discrete wavelet transform (DWT) are supposed as virtual images and each of them is divided into eight polar sectors. Then, the curve length of each excerpted segment is calculated and is used as the element of the feature space. To increase the robustness of the proposed classification algorithm versus noise, artifacts and arrhythmic outliers, a fusion structure consisting of three Multi Layer Perceptron-Back Propagation (MLP-BP) neural networks with different topologies and one Adaptive Network Fuzzy Inference System (ANFIS) were designed and implemented. To show the merit of the new proposed algorithm, it was applied to all MIT-BIH Arrhythmia Database records and the discrimination power of the classifier in isolation of different beat types of each record was assessed and as the result, the average accuracy value Acc=98.27% was obtained. Also, the proposed method was applied to 8 number of arrhythmias (Normal, LBBB, RBBB, PVC, APB, VE, PB, VF) belonging to 19 number of the aforementioned database and the average value of Acc=98.08% was achieved. To evaluate performance quality of the new proposed hybrid learning machine, the obtained results were compared with similar peer-reviewed studies in this area.

---

Two-dimensional (TD) adaptive filtering is a technique that can be applied to many image, and signal processing applications. This paper extends the one-dimensional adaptive filter algorithms to TD structures and the novel TD adaptive filters are established. Based on this extension, the TD variable step-size normalized least mean squares (TD-VSS-NLMS), the TD-VSS affine projection algorithms (TD-VSS-APA), the TD set-membership NLMS (TD-SM-NLMS), the TD-SM-APA, the TD selective partial update NLMS (TD-SPU-NLMS), and the TD-SPU-APA are presented. In TD-VSS adaptive filters, the step-size changes during the adaptation which leads to improve the performance of the algorithms. In TD-SM adaptive filter algorithms, the filter coefficients are not updated at each iteration. Therefore, the computational complexity is reduced. In TD-SPU adaptive algorithms, the filter coefficients are partially updated which reduce the computational complexity. We demonstrate the good performance of the proposed algorithms thorough several simulation results in TD adaptive noise cancellation (TD-ANC) for image restoration. The results are compared with the classical TD adaptive filters such as TD-LMS, TD-NLMS, and TD-APA

---

When the process is highly uncertain, even linear minimum phase systems must sacrifice desirable feedback control benefits to avoid an excessive ‘cost of feedback’, while preserving the robust stability. In this paper, the problem of supervisory based switching Quantitative Feedback Theory (QFT) control is proposed for the control of highly uncertain plants. According to this strategy, the uncertainty region is suitably divided into smaller regions. It is assumed that a QFT controller-prefilter exits for robust stability and performance of the individual uncertain sets. The proposed control architecture is made up by these local controllers, which commute among themselves in accordance with the decision of a high level decision maker called the supervisor. The supervisor makes the decision by comparing the candidate local model behavior with the one of the plant and selects the controller corresponding to the best fitted model. A hysteresis switching logic is used to slow down switching for stability reasons. Besides, each controller is designed to be stable in the whole uncertainty domain, and as accurate in command tracking as desired in its uncertainty subset to preserve the robust stability from any failure in the switching.

---

Islanded operation of distributed generators is a problem that can take place when they are connected to a distribution system. In this paper an islanding detection method is presented for inverter based distributed generation (DG) using under/over voltage relay. The method is an adaptive one and is based on the change of DG active power reference (Pref) in inverter control interface. The active power reference has a fixed value in normal condition, whereas, if the point of common coupling (PCC) voltage changes, Pref has determined as a linear function of voltage. The slope of Pref is dependent to the load active power (Pload) and should be changed if Pload changes. The non-detection zone (NDZ) of the proposed method is dependent on the accuracy of the voltage measurement equipment if changing of the PCC voltage is sensed, then, islanding will be detected if it is occurred. Also it does not have any negative effects on the distribution system in normal conditions. Moreover, the proposed technique can be applied when two-DG is in the island. The proposed method is evaluated according to the requirements of the IEEE 1547 and UL 1741 standards, using PSCAD/EMTDC software.

---

This paper presents a new variable step-size normalized subband adaptive filter (VSS-NSAF) algorithm. The proposed algorithm uses the prior knowledge of the system impulse response statistics and the optimal step-size vector is obtained by minimizing the mean-square deviation(MSD). In comparison with NSAF, the VSS-NSAF algorithm has faster convergence speed and lower MSD. To reduce the computational complexity of VSSNSAF, the VSS selective partial update NSAF (VSS-SPU-NSAF) is proposed where the filter coefficients are partially updated in each subband at every iteration. We demonstrated the good performance of the proposed algorithms in convergence speed and steady-state MSD for a system identification set-up.

---

This paper proposes a new bilateral control scheme to ensure both transparency and robust stability under unknown constant time delay in stiff environment. Furthermore, this method guaranties suitable performance and robust stability when transition occurs between soft and stiff environments. This framework is composed of an adaptive sliding mode controller and an adaptive impedance controller, where online estimation of the environment impedance is performed, and then used as the desired impedance at the master side. Numerical simulations are provided to verify the theoretical results under different conditions, such as constant and time-varying delay, obstructed environment and transitioning between soft and stiff environment. Afterwards, comparison with a recent work is addressed.

---

This paper presents new adaptive filtering techniques used in speech enhancement system. Adaptive filtering schemes are subjected to different trade-offs regarding their steady-state misadjustment, speed of convergence, and tracking performance. Fractional Least-Mean-Square (FLMS) is a new adaptive algorithm which has better performance than the conventional LMS algorithm. Normalization of LMS leads to better performance of adaptive filter. Furthermore, convex combination of two adaptive filters improves its performance. In this paper, new convex combinational adaptive filtering methods in the framework of speech enhancement system are proposed. The proposed methods utilize the idea of normalization and fractional derivative, both in the design of different convex mixing strategies and their related component filters. To assess our proposed methods, simulation results of different LMS-based algorithms based on their convergence behavior (i.e., MSE plots) and different objective and subjective criteria are compared. The objective and subjective evaluations include examining the results of SNR improvement, PESQ test, and listening tests for dual-channel speech enhancement. The powerful aspects of proposed methods are their low complexity, as expected with all LMS-based methods, along with a high convergence rate.

---

In this paper, a novel stator current based Model Reference Adaptive System (MRAS) estimator for speed estimation in the speed-sensorless vector controlled induction motor drives is presented. In the proposed MRAS estimator, measured stator current of the induction motor is considered as a reference model. The estimated stator current is produced in an adjustable model to compare with the measured stator current, where rotor flux identification is needed for stator current estimation. In the available stator current based MRAS estimator, rotor flux is estimated by the use of measured stator current, where the adjustable model and reference model depend on each other since measured stator current is employed in both of them. To improve the performance of the MRAS speed estimator, both the stator current and rotor flux are estimated in the adjustable model by using the state space equations of the induction motor, adjusted with the rotor speed calculated by an adaptation mechanism. The stability of the proposed MRAS estimator is studied through a small signal analysis. Senorless induction motor drive along with the proposed MRAS speed estimator is verified through computer simulations. In addition, performance of the proposed MRAS is compared with the available stator current based MRAS speed estimator

---

This paper presents a simple and easy implementable Least Mean Square (LMS) type approach for frequency estimation of three phase power system in an unbalanced condition. The proposed LMS type algorithm is based on a second order recursion for the complex voltage derived from Clarke's transformation which is proved in the paper. The proposed algorithm is real adaptive filter with real parameter (not complex) which can be efficiently implemented by DSP. In unbalanced situations, simulation experiments show the advantages and drawbacks of the proposed algorithm in comparison to Complex LMS (CLMS) and Augmented Complex LMS (ACLMS) methods

---

The Global Positioning System (GPS) signals are very weak signal over wireless channels, so they are vulnerable to in-band interferences. Therefore, even a low-power interference can easily spoof GPS receivers. Among the variety of GPS signal interference, spoofing is considered as the most dangerous intentional interference. The spoofing effects can mitigate with an appropriate strategy in the receiver. In this paper, we use methods of adaptive filter based on Least Mean Squares (LMS) and Normalized Least Mean Squares (NLMS) algorithms in-order to defense against spoofing. The proposed techniques are applied in the acquisition stage of the receiver. The proposed methods have been implemented on real dataset. The results explain that the suggested algorithms significantly decrease spoofing. Also, they improve Position Dilution of Precision (PDOP) parameter. Based on the results, NLMS algorithm has better performance than LMS algorithm.