9214943
A restart univariate estimation of distribution algorithm: sampling under mixed Gaussian and Lévy probability distribution
A univariate EDA denoted as ldquoLSEDA-glrdquo for large scale global optimization (LSGO) problems is proposed in this paper. Three efficient strategies: sampling under mixed Gaussian and Levy probability distribution, standard deviation control strategy and restart strategy are adopted to improve the performance of classical univariate EDA on LSGO problems. The motivation of such work is to extend EDAs to LSGO domain reasonably. Comparison among LSEDA-gl, EDA with standard deviation control strategy only (EDA-STDC) and similar EDA version ldquocontinuous univariate marginal distribution algorithmrdquo UMDAc is carried out on classical test functions. Based on the general comparison standard, the strengths and weaknesses of the algorithms are discussed. Besides, LSEDA-gl is tested on 7 functions with 100, 500, 1000 dimensions provided in the CECpsila2008 Special Session on LSGO. This work is also expected to provide a comparison result for the CECpsila2008 special session.
26519336
Iris Recognition Algorithm Using Modified Log-Gabor Filters
In this paper, we presented an iris recognition algorithm based on modified Log-Gabor filters. The algorithm is similar as the method proposed by Daugman in general procedure while modified Log-Gabor filters are adopted to extract the iris phase information instead of complex Gabor filters used in Daugman's method. The advantage of Log-Gabor filters over complex Gabor filters is the former are strictly bandpass filters and the latter are not. The property of strictly bandpass makes the Log-Gabor filters more suitable to extract the iris phase features regardless of the background brightness. The comparison experiments between complex Gabor filters based methods and the proposed method are also presented in this paper
3197098
A Multi-Objective Hw-sw Co-Synthesis Algorithm Based on Quantum-Inspired Evolutionary Algorithm
Hardware–Software (HW–SW) co-synthesis is one of the key steps in modern embedded system design. Generally, HW–SW co-synthesis is to optimally allocate processors, assign tasks to processors, and schedule the processing of tasks to achieve a good balance among performance, cost, power consumption, etc. Hence, it is a typical multi-objective optimization problem. In this paper, a new multi-objective HW–SW co-synthesis algorithm based on the quantum-inspired evolutionary algorithm (MQEAC) is proposed. MQEAC utilizes multiple quantum probability amplitude vectors to model the promising areas of solution space. Meanwhile, this paper presents a new crossover operator to accelerate the convergence to the Pareto front and introduces a PE slot-filling strategy to improve the efficiency of scheduling. Experimental results show that the proposed algorithm can solve the typical multi-objective co-synthesis problems effectively and efficiently.
29843270
A Self-adaptive Mixed Distribution Based Uni-variate Estimation of Distribution Algorithm for Large Scale Global Optimization
Large scale global optimization (LSGO), which is highly needed for many scientific and engineering applications, is a very important and very difficult task in optimization domain. Various algorithms have been proposed to tackle this challenging problem, but the use of estimation of distribution algorithms (EDAs) to it is rare. This chapter aims at investigating the behavior and performances of uni-variate EDAs mixed with different kernel probability densities via fitness landscape analysis. Based on the analysis, a self-adaptive uni-variate EDA with mixed kernels (MUEDA) is proposed. To assess the effectiveness and efficiency of MUEDA, function optimization tasks with dimension scaling from 30 to 1500 are adopted. Compared to the recently published LSGO algorithms, MUEDA shows excellent convergence speed, final solution quality and dimensional scalability.
14435465
A hardware/software partitioning algorithm based on artificial immune principles
Hardware/software codesign is the main approach to designing the embedded systems. One of the primary steps of the hardware/software codesign is the hardware/software partitioning. A good partitioning scheme is a tradeoff of some constraints, such as power, size, performance, and so on. Inspired by both negative selection model and evolutionary mechanism of the biological immune system, an evolutionary negative selection algorithm for hardware/software partitioning, namely ENSA-HSP, is proposed in this paper. This ENSA-HSP algorithm is proved to be convergent, and its ability to escape from the local optimum is also analyzed. The experimental results demonstrate that ENSA-HSP is more efficient than traditional evolutionary algorithm.
17592710
Full-Space LDA With Evolutionary Selection for Face Recognition
Linear discriminant analysis (LDA) is a popular feature extraction technique for face recognition. However, it often suffers from the small sample size problem when dealing with the high dimensional face data. Some approaches have been proposed to overcome this problem, but they usually utilize all eigenvectors of null or range subspaces of within-class scatter matrix (Sw). However, experimental results testified that not all the eigenvectors in the full space of S w are positive to the classification performance, some of which might be negative. As far as we know, there have been no effective ways to determine which eigenvectors should be adopted. This paper proposes a new method EDA+Full-space LDA, which takes full advantage of the discriminative information of the null and range subspaces of Sw by selecting an optimal subset of eigenvectors. An estimation of distribution algorithm (EDA) is used to pursuit a subset of eigenvectors with significant discriminative information in full space of Sw middot EDA+Full-space LDA is tested on ORL face image database. Experimental results show that our method outperforms other LDA methods
16772027
CCL-SVC: Optimizing user experience of broadcasting video on computation capability limited handheld devices
In this paper, we propose a novel scheme using computing complexity layered scalable video coding (CCLSVC) to optimize the user experience of broadcasting video in the computing capability limited handheld terminals. To address the heterogeneity of computing capability among different handheld devices, we employ hierarchal B reference structure of SVC to divide the frames into multiple computing complexity layers (CC Layers) in server side. The handheld clients simply choose to decode the frames in their corresponding layers in terms of their computation capability to maximize the video PSNR. We have proved that the optimal CC Layers division problem is a precedence constrained scheduling problem, which is an NP-complete problem. And we further propose our fast greedy method to approximately get optimized broadcasting video playback PSNR. The simulation shows that our method is superior to temporal SVC and random frame discarding method.
20301405
Unequal-arm Adaptive Rood Pattern Search with Early Terminations For Fast Block-matching Motion Estimation on H.264
Based on a rood-shaped pattern of the motion-vector displacement distribution inherently resulted from block-matching motion estimation, a series of adaptive rood pattern search (ARPS) algorithms have been introduced. Among them, the unequal-arm ARPS has achieved superior performance on many accounts while maintaining a fairly close rate-distortion performance compared with that of the full search. In this paper, an enhanced version of the unequal-arm ARPS is introduced by incorporating early terminations at both the initial search and the refined local search stages. Its performance was compared with that of the UMHexagonS fast block-matching motion estimation algorithm based on the JM-9.3 software encoder. The experimental results show that the unequal-arm ARPS with early terminations has yielded significant search efficiency gain while consistently maintaining a fairly close rate-distortion performance compared with that of the UMHexagonS. Furthermore, the proposed algorithm is fairly simple on implementation
15051068
Study on Epipolar Geometry Restoration of Parallel Binocular Vision
The epipolar geometry restoration offline and online for the parallel binocular vision system were discussed in this paper. For the former, a method that uses a common calibration board to realize automatic and accurate matching of the image corner pairs was developed; for the latter, a connotative constraint was proved by geometry theory and the corresponding cross-correlation sparse matching algorithm was introduced. The constraint was that for any space point projected into two images, the horizontal coordinate in the left image of this point is bigger than that in the right image. Standard and real images experiments were made for each kind of problem and the results show that the algorithms for each problem were valid.
3471440
Universal JPEG steganalysis based on microscopic and macroscopic calibration
In this paper, we present a new universal steganalysis scheme to effectively attack some recently proposed JPEG steganography. Different from the other steganalyzers, not only the magnitude but also the sign dependencies existed in intra-block and inter-block quantized DCT (discrete cosine transform) coefficients are exploited by the Markov empirical transition matrices. Moreover, a new microscopic and macroscopic calibration method is proposed to calibrate the local and global distribution of the quantized DCT coefficients of the test image, thus improve the detecting performance. Experimental results demonstrate that our proposed scheme outperforms some existing steganalyzers in attacking the advanced JPEG steganography such as F5, MB1 and Outguess.
10259496
An E-Government Platform Based on Multi-Tier Architecture
With the development of dynamic e-government and the network, the application system becomes more complicated. Traditional e-government system will have an inherent scalability problem as the number of applications increases continuously. To solve this problem, an e-government platform based on multi-tier architecture is presented. By integrating applications, resources and system modules, the platform provides an effective mechanism to reduce the development and communication cost. This paper intensively discusses the design rationale and practical solutions of the platform, including structured data models, a secure data exchange model, uniform interface specifications, a topic based publish/subscribe communication mechanism and an asynchronous execution mechanism. The security of the platform is also evaluated by formal logic method.