Frontiers of Electrical and Electronic Engineering

ISSN 2095-2732

ISSN 2095-2740(Online)

CN 10-1028/TM

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, Volume 7 Issue 2

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EDITORIAL
RESEARCH ARTICLE
An extended SHESN with leaky integrator neuron and inhibitory connection for Mackey-Glass prediction
Bo YANG, Zhidong DENG
Front Elect Electr Eng. 2012, 7 (2): 200-207.  
https://doi.org/10.1007/s11460-011-0176-5

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Echo state network (ESN) proposed by Jaeger in 2001 has remarkable capabilities of approximating dynamics for complex systems, such as Mackey-Glass problem. Compared to that of ESN, the scale-free highly-clustered ESN, i.e., SHESN, which state reservoir has both small-world phenomenon and scale-free feature, exhibits even stronger approximation capabilities of dynamics and better echo state property. In this paper, we extend the state reservoir of SHESN using leaky integrator neurons and inhibitory connections, inspired from the advances in neurophysiology. We apply the extended SHESN, called e-SHESN, to the Mackey-Glass prediction problem. The experimental results show that the e-SHESN considerably outperforms the SHESN in prediction capabilities of the Mackey-Glass chaotic time-series. Meanwhile, the interesting complex network characteristic in the state reservoir, including the small-world property and the scale-free feature, remains unchanged. In addition, we unveil that the original SHESN may be unstable in some cases. However, the proposed e-SHESN model is shown to be able to address the flaw through the enhancement of the network stability. Specifically, by using the ridge regression instead of the linear regression, the stability of e-SHESN could be much more largely improved.

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A sparse representation-based approach for video copy detection
Jianmin LI, Chen SUN, Bo ZHANG
Front Elect Electr Eng. 2012, 7 (2): 208-215.  
https://doi.org/10.1007/s11460-011-0171-x

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Content-based video copy detection becomes an active research field due to requirement of copyright protection, business intelligence, video retrieval, etc. Although it is assumed in the existing methods that reference database consists of original videos, these videos are difficult to be obtained in many practical cases. In this paper, a copy detection method based on sparse representation is proposed to make use of some imperfect prototypes of original videos maintained in the reference database. A query video is represented as a linear combination of all the videos in the database. Then we can determine that whether the query has sibling videos in the database based on distribution of coefficients and find them out based on reconstruction error. The experiments show that even with very limited dimensional feature, this method can achieve high performance.

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A fast-convergence distributed support vector machine in small-scale strongly connected networks
Hua XU, Yun WEN, Jixiong WANG
Front Elect Electr Eng. 2012, 7 (2): 216-223.  
https://doi.org/10.1007/s11460-011-0172-9

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In this paper, a fast-convergence distributed support vector machine (FDSVM) algorithm is proposed, aiming at efficiently solving the problem of distributed SVM training. Rather than exchanging information only among immediate neighbor sites, the proposed FDSVM employs a deterministic gossip protocol-based communication policy to accelerate diffusing information around the network, in which each site communicates with others in a flooding and iterative manner. This communication policy significantly reduces the total number of iterations, thus further speeding up the convergence of the algorithm. In addition, the proposed algorithm is proved to converge to the global optimum in finite steps over an arbitrary strongly connected network (SCN). Experiments on various benchmark data sets show that the proposed FDSVM consistently outperforms the related state-of-the-art approach for most networks, especially in the ring network, in terms of the total training time.

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Action recognition from arbitrary views using 3D-key-pose set
Junxia GU, Xiaoqing DING, Shenjing WANG
Front Elect Electr Eng. 2012, 7 (2): 224-241.  
https://doi.org/10.1007/s11460-011-0175-6

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Recovering three-dimensional (3D) human pose sequence from arbitrary view is very difficult, due to loss of depth information and self-occlusion. In this paper, view-independent 3D-key-pose set is selected from 3D action samples, for the purpose of representing and recognizing those same actions from a single or few cameras without any restriction of the relative orientations between cameras and subjects. First, 3D-key-pose set is selected from the 3D human joint sequences of 3D training action samples that are built from multiple viewpoints. Second, 3D key pose sequence, which matches best with the observation sequence, is selected from the 3D-key-pose set to represent the observation sequence of arbitrary view. 3D key pose sequence contains many discriminative view-independent key poses but cannot accurately describe pose of every frame in the observation sequence. Considering the above reasons, pose and dynamic of action are modeled respectively in this paper. Exemplar-based embedding and probability of unique key pose are applied to model pose property. Complementary dynamic feature is extracted to model these actions that share the same poses but have different dynamic features. Finally, these action models are fused to recognize observation sequence from a single or few cameras. Effectiveness of the proposed approach is demonstrated with experiments on IXMAS dataset.

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Can prior knowledge help graph-based methods for keyword extraction?
Zhiyuan LIU, Maosong SUN
Front Elect Electr Eng. 2012, 7 (2): 242-253.  
https://doi.org/10.1007/s11460-011-0174-7

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Graph-based methods are one of the widely used unsupervised approaches for keyword extraction. In this approach, words are linked according to their co-occurrences within the document. Afterwards, graph-based ranking algorithms are used to rank words and those with the highest scores are selected as keywords. Although graph-based methods are effective for keyword extraction, they rank words merely based on word graph topology. In fact, we have various prior knowledge to identify how likely the words are keywords. The knowledge of words may be frequency-based, position-based, or semantic-based. In this paper, we propose to incorporate prior knowledge with graph-based methods for keyword extraction and investigate the contributions of the prior knowledge. Experiments reveal that prior knowledge can significantly improve the performance of graph-based keyword extraction. Moreover, by combining prior knowledge with neighborhood knowledge, in experiments we achieve the best results compared to previous graph-based methods.

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Using log mining to analyze user behavior on search engine
Ke XIE, Huijia YU, Rongwei CEN
Front Elect Electr Eng. 2012, 7 (2): 254-260.  
https://doi.org/10.1007/s11460-011-0177-4

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Users’ behavior analysis has become one of the most important research topics, especially in terms of performance optimization, architecture analysis, and system maintenance, due to the rapid growth of search engine users. By adequately performing analysis on log data, researchers and Internet companies can get guidance to better search engines. In this paper, we perform our analysis based on approximately 750 million entries of search requests obtained from log of a real commercial search engine. Several aspects of users’ behavior are studied, including query length, ratio of query refining, recommendation access, and so on. Different information needs may lead to different behaviors, and we address this discussion in this paper. We firmly believe that these analyses would be helpful with respect of improving both effectiveness and efficiency of search engines.

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Wireless multicarrier digital transmission via frames: Capacity analysis and optimization design
Fangming HAN, Xianda ZHANG
Front Elect Electr Eng. 2012, 7 (2): 261-269.  
https://doi.org/10.1007/s11460-011-0173-8

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By treating information transmission as tiling over the time-frequency plane, we propose a digital signal transmission scheme employing overcomplete frames as modulation pulses. The new scheme can achieve a signaling rate larger than the Nyquist rate. We first analyze the capacity performance of the frame transmission scheme over additive white Gaussian noise (AWGN) channels. It proves that the proposed scheme can achieve the Shannon capacity asymptotically. Next, we design the Gabor frame system parameters in time-frequency dispersive channels. It is shown that the pulses shape and the time-frequency separation should be matched to the channel dispersion parameters to achieve the minimum energy perturbation. Numerical results are presented to verify the theoretical findings.

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Maximal terminal region approach for MPC using subsets sequence
Yafeng WANG, Fuchun SUN, Huaping LIU, Dongfang YANG
Front Elect Electr Eng. 2012, 7 (2): 270-278.  
https://doi.org/10.1007/s11460-012-0178-y

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For the sake of enlarging the domain of attraction of model predictive control (MPC), a novel approach of gradually approximating the maximal terminal state region is proposed in this paper. Given the terminal cost, both surrounding set sequence and subsets sequence of the maximal terminal region were constructed by employing one-step set expansion iteratively. It was theoretically proved that when the iteration time goes to infinity, both the surrounding set sequence and the subsets sequence will converge to the maximal terminal region. All surrounding and subsets sets in these sequences are extracted from the state space by exploiting support vector machine (SVM) classifier. Finally, simulations are implemented to validate the effectiveness of this approach.

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9 articles