A new algorithm called Signal Subspace Extraction is presented for detecting and estimating the target echo in *** new algorithm maintains the bene-fit of the Principal Component Inverse algorithm,moreover shows bette...
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A new algorithm called Signal Subspace Extraction is presented for detecting and estimating the target echo in *** new algorithm maintains the bene-fit of the Principal Component Inverse algorithm,moreover shows better performance with a more reasonable reverberation ***,a block forward matrix is proposed to extend the algorithm to the space-time array *** new algorithm also allows good echo *** are presented using both real,activesonar data and simulated data.
An algorithm to blindly detect frequency hopping (FH) signals corrupted by white Gaussian noise (WGN) is presented. Any parameters of FH are assumed to be unknown, and the noise power can be either known or unknown. T...
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An algorithm to blindly detect frequency hopping (FH) signals corrupted by white Gaussian noise (WGN) is presented. Any parameters of FH are assumed to be unknown, and the noise power can be either known or unknown. The algorithm is based on the difference in cyclostationarity (CS) between FH signal and WGN. The module of estimation of cyclic autocorrelation is picked up with available received signal as the test statistic. A WGN of which power equals to the average power of received signal is constructed at the received end, and then the maximum module of estimation of cyclic autocorrelation is computed with this WGN as the detection threshold. Simulation results have proved that the proposed algorithm is adequate to the environments in which signal-to-noise ratio (SNR) is higher than -3dB.
In many application suck as face detection or recognition a major phase would be eye detection. In addition, its wide use as a part of serious applications, made it an important task should be worked on. Using color c...
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In many application suck as face detection or recognition a major phase would be eye detection. In addition, its wide use as a part of serious applications, made it an important task should be worked on. Using color characteristics is a useful way to detect eyes. We use special color space, YCbCr which its components give us worthwhile information about eyes. We make two maps according to its components and merge them to obtain a final map. Candidates are generated on this final map. We apply an extra phase on candidates to determine suitable eye pair. The extra phase consists of flexible thresholding and geometrical tests. Flexible thresholding makes generating candidates more carefully and geometrical tests allow proper candidates to be selected as eyes. Simulation results on CVI and Iranian Databases showed this phase improved the correct detection rate by about 12.4% and reach 98.5% success rate on the average.
This study focuses on testing and improving the available scene change detection methods developed for bit streams compressed with the latest coding standard H.264/AVC.
This study focuses on testing and improving the available scene change detection methods developed for bit streams compressed with the latest coding standard H.264/AVC.
With the development of WSNs in the military and commercial fields, the security of WSNs is becoming more and more important. The security threats of wireless sensor networks (WSNs) come from not only the attacks of e...
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With the development of WSNs in the military and commercial fields, the security of WSNs is becoming more and more important. The security threats of wireless sensor networks (WSNs) come from not only the attacks of external attackers but also the byzantine behaviors and selfish behaviors of internal nodes. The classical security mechanisms, namely cryptography and authentication, can prevent some outsider attacks, however, they are noneffective to the attacks and the anomaly behaviors of internal nodes. A reputation-based model for malicious node detection in WSNs is proposed in this paper. In this model, the beta distribution is used to describe the reputation distribution, and the indirect reliability of third-party nodes is introduced. The simulation results show that the proposed model has better performance in terms of resisting the malicious deceit behaviors of high credit-grade nodes.
This paper investigates a two-dimensionally spread orthogonal frequency and code division multiplexing (OFCDM) system with multi-code transmission and multiple input multiple output (MIMO) multiplexing, where desired ...
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This paper investigates a two-dimensionally spread orthogonal frequency and code division multiplexing (OFCDM) system with multi-code transmission and multiple input multiple output (MIMO) multiplexing, where desired data signals are interfered by not only co-channel signals from other transmit antennas (or multi-antenna interference (MAI)), but also multi- code interference (MCI) from other code channels on the same antenna. Combining the iterative detection in the space domain and the hybrid MCI cancellation and minimum mean square error (MMSE) detection in the frequency domain, a joint iterative detection algorithm is proposed to cancel out MAI and MCI. For the 0 th loop of the joint iterative detection, a 2-stage hybrid detection is needed in the frequency domain, while for later loops, a 0-stage hybrid detection or pure MMSE is sufficient. The system performance improves as the number of loops in the joint iterative detection increases. Moreover, using joint iterative detection, larger frequency diversity gain can be achieved and the performance improves as the frequency domain spreading factor increases.
Biorthogonal spline wavelet is used to detect the QRS complex of ECG signal. Mallat algorithm is applied in the decomposition of ECG signal by using the equivalent filter of a biorthogonal spline wavelet. Lipschitz ex...
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Biorthogonal spline wavelet is used to detect the QRS complex of ECG signal. Mallat algorithm is applied in the decomposition of ECG signal by using the equivalent filter of a biorthogonal spline wavelet. Lipschitz exponent is introduced to investigate the relationship between the signal singularity (R Peak) and the zero-crossing point of the modulus maximum pair of the signal's wavelet transform. Adaptive threshold, refractory period and expiating are applied to improve the anti-interference performance. Experimental results demonstrated that this method is robust against time varying characteristics of QRS complex and noise. A correct detection rate of 99.905% has been achieved when the MIT-BIH arrhythmia database is used to test the proposed QRS complex detection algorithm.
This paper presents a distributed algorithm for critical area detection in satellite imagery. The detection of critical area is very important in natural disaster detection and control. The algorithm uses the distribu...
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This paper presents a distributed algorithm for critical area detection in satellite imagery. The detection of critical area is very important in natural disaster detection and control. The algorithm uses the distributed change detection methods for multiple spectral bands in satellite images and combines changes which have appeared during a period of time. The result shows a critical area for analyzed time interval. The algorithm is distributed for support a large amount of data. The distributed approach shows a decrease in processing time with the increase of the number of workers. The presented algorithm represents a component from MedioGRID system, which implemented a real-time satellite image processing system for extracting relevant environmental and meteorological parameters on Grid systems. The critical area detection application will be integrated in Grid environments.
Traditional outlier detection algorithms are designed to apply to centralized databases, not distributed databases. We proposed a novel outlier detection algorithm for distributed databases. Given data assigned to dif...
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Traditional outlier detection algorithms are designed to apply to centralized databases, not distributed databases. We proposed a novel outlier detection algorithm for distributed databases. Given data assigned to different network nodes of a network platform, where each node has its own memory and hard disc, and the communication between nodes driven by message, the populated data would be non-overlapping. The working way of the network system is a manager-worker mode, that is, that a node as manager is responsible for assigning tasks to worker and querying the results from worker nodes. The algorithm first detected local outliers based on distance on all nodes, and then identified local outliers collected in the central node where a globally screening operation on all local outliers was implemented to achieve really global outliers. To scale the algorithm to massive data and reduce its computing complexity, a data filtering technology was further presented. Experimental results demonstrated that the algorithm effectively and efficiently handled on real and artificial data.
A fast and effective fade detection algorithm is proposed in this paper, which directly operates in compressed domain and suitable for real-time implementation. By analyzing the prediction directions of B frames, whic...
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A fast and effective fade detection algorithm is proposed in this paper, which directly operates in compressed domain and suitable for real-time implementation. By analyzing the prediction directions of B frames, which are revealed in the macroblock types, the candidate fades can be found. Then, uncommon intracoded macroblocks of the P frame can be applied as an indicator of fade. As a result, locating fades are operated by a sliding window. Extensive experiments illustrate that the proposed algorithm achieves superiority measured by recall and precision rates, providing a useful technique for fast and on-line video content processing.
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