Iranian Journal of Electrical and Electronic Engineering

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The concepts of robust classification and intelligently controlling the search process of genetic algorithm (GA) are introduced and integrated with a conventional genetic classifier for development of a new version of it, which is called Intelligent and Robust GA-classifier (IRGA-classifier). It can efficiently approximate the decision hyperplanes in the feature space. It is shown experimentally that the proposed IRGA-classifier has removed two important weak points of the conventional GA-classifiers. These problems are the large number of training points and the large number of iterations to achieve a comparable performance with the Bayes classifier, which is an optimal conventional classifier. Three examples have been chosen to compare the performance of designed IRGA-classifier to conventional GA-classifier and Bayes classifier. They are the Iris data classification, the Wine data classification, and radar targets classification from backscattered signals. The results show clearly a considerable improvement for the performance of IRGA-classifier compared with a conventional GA-classifier.

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Automatic signal type identification (ASTI) is an important topic for both the civilian and military domains. Most of the proposed identifiers can only recognize a few types of digital signal and usually need high levels of SNRs. This paper presents a new high efficient technique that includes a variety of digital signal types. In this technique, a combination of higher order moments and higher order cumulants (up to eighth) are proposed as the effective features. A hierarchical support vector machine based structure is proposed as the classifier. In order to improve the performance of identifier, a genetic algorithm is used for parameters selection of the classifier. Simulation results show that the proposed technique is able to identify the different types of digital signal (e.g. QAM128, ASK8, and V29) with high accuracy even at low SNRs.

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Chaos based communications have drawn increasing attention over the past years. Chaotic signals are derived from non-linear dynamic systems. They are aperiodic, broadband and deterministic signals that appear random in the time domain. Because of these properties, chaotic signals have been proposed to generate spreading sequences for wide-band secure communication recently. Like conventional DS-CDMA systems, chaos-based CDMA systems suffer from multi-user interference (MUI) due to other users transmitting in the cell. In this paper, we propose a novel method based on radial basis function (RBF) for both blind and non-blind multiuser detection in chaos-based DS-CDMA systems. We also propose a new method for optimizing generation of binary chaotic sequences using Genetic Algorithm. Simulation results show that our proposed nonlinear receiver with optimized chaotic sequences outperforms in comparison to other conventional detectors such as a single-user detector, decorrelating detector and minimum mean square error detector, particularly for under-loaded CDMA condition, which the number of active users is less than processing gain.

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In recent years chaotic secure communication and chaos synchronization have received ever increasing attention. Unfortunately, despite the advantages of chaotic systems, Such as, noise-like correlation, easy hardware implementation, multitude of chaotic modes, flexible control of their dynamics, chaotic self-synchronization phenomena and potential communication confidence due to the very dynamic properties of chaotic nonlinear systems, the performance of most of such designs is not studied and so is not still suitable for wireless channels. To overcome this problem, in this paper a novel wide-band chaos-based communication scheme in multipath fading channels is presented, where the chaotic synchronization is implemented by particle filter observer. To illustrate the effectiveness of the proposed scheme, numerical simulations based on particle filter are presented in different channel conditions and the results are compared with two other EKF and UKF based communication scheme. Simulation results show the Remarkable BER performance of the proposed particle filter-based system in both AWGN and multipath fading channels condition, causes this idea act as a good candidate for asynchronous wide band communication.

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Unintentional attacks on watermarking schemes lead to degrade the watermarking channel, while intentional attacks try to access the watermarking channel. Therefore, watermarking schemes should be robust and secure against unintentional and intentional attacks respectively. Usual security attack on watermarking schemes is the Known Message Attack (KMA). Most popular watermarking scheme with structured codebook is the Scalar Costa Scheme (SCS). The main goal of this paper is to increase security and robustness of SCS in the KMA scenario. To do this, SCS model is extended to more general case. In this case, the usual assumption of an infinite Document to Watermark Ratio (DWR) is not applied. Moreover watermark is assumed to be an arbitrary function of the quantization noise without transgressing orthogonality as in the Costa’s construction. Also, this case is restricted to the structured codebooks. The fundamental trade-off is proved between security and robustness of Generalized SCS (GSCS) in the KMA scenario. Based on this trade-off and practical security attack on SCS, a new extension of SCS is proposed which is called Surjective-SCS (SSCS). In the absence of robustness attack, the SSCS has more security than SCS in the same DWR. However, the SSCS achieves more security and robustness than SCS only in low Watermark to Noise Ratio (WNR) regime or low rate communications.

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In this paper, five conditions that have been proposed by Cobb and Shenoy are studied for nine different mappings from the Dempster-Shafer theory to the probability theory. After comparing these mappings, one of the considerable results indicates that none of the mappings satisfies the condition of invariance with respect to the marginalization process. In more details, the main reason for this defect is that the classic projection process in DST loses some probabilistic information. Therefore, as regards this subject, a solution is presented for solving this problem for two mappings: the pignistic probability and the normalized plausibility transformation.