Journal of Applied Sciences

Uniqueness of Radio Frequency Fingerprint

YUAN Hong-lin HU Ai-qun;CHEN Kai-zhi

2009, 27(1): 1-5 .

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Uniqueness of radio frequency fingerprint is the foundation of transmitter recognition based on RF fingerprint. Mathematical model of RF fingerprint recognition system is constructed based on equivalent components having the same effect with overall transmitter components with manufacturing tolerance and drift tolerance. It is shown based on the model that component manufacturing tolerance, drift tolerance and ADC precision are principal influence factors of uniqueness of RF fingerprint. The tolerance-factor is validated in experiments. The results indicate that RF fingerprint is potentially unique.

Suboptimal Degree Distribution Algorithm of LT Codes of Digital Fountain

ZHU Hong-peng;ZHANG Geng-xin;XIE Zhi-dong

2009, 27(1): 6-11 .

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Degree distribution is key to the decoding efficiency of LT codes. With analysis of the variation of preprocessing set, this paper proposes the Optimal Degree Distribution (ODD) of LT codes and analyzes its drawbacks in realization. On the basis of ODD, a practical Suboptimal Degree Distribution (SODD) is put forward. Through testing, with respect to the mean value, the top value and variance of decoding efficiencies, LT codes with SODD perform better than that with Robust Soliton Degree Distribution. The conclusion of research is practically valuable in improving efficiencies of data distribution applications.

A Game Model of Combination Strategy for Routing Nodes in P2P Networks

WANG Hao-yun;ZHANG Shun-yi;SUN Yan-fei;LI Jun

2009, 27(1): 12-18 .

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The existing studies on the game model of P2P nodes do not take into account diversity of nodes types,complexity of node strategies, and asymmetry of node information. This paper presents a game model of combination strategy for routing nodes in P2P networks. In this model, routing nodes are divided into two types, namely good nodes and bad nodes. They are also categorized as end nodes and middle nodes according to their positions in the routing process. The corresponding strategies adopted by each type of nodes at each routing stage are defined as combination strategies of routing nodes. Based on such strategies, this paper analyzes payoff matrixes of the games among various node strategies, and derives transfer conditions of different combination strategies in the game model with asymmetric information and betrayal of routing nodes.

Modulation Classification Using Weighted Constellation Matching

ZHANG Lu-ping;WANG Jian-xin

2009, 27(1): 19-23 .

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Limitation of existing modulation classification based on constellation is studied, and an improved technique proposed. Eleven kinds of signals are divided into three groups with two higher-order moments. Fuzzy C-means clustering is applied to recover the unknown constellations. The recovered constellations are then matched with standard constellations and classified using an improved cost function. Simulation results show that the correct
identification rate is high even if there are more constellation candidates, with the average recognition rate being improved by more than 25% at SNR of 10 dB.

Capacity of CDMA and FDMA for Multi-beam GEO Satellite Communications

HAO Xie-dong;LIU Ai-jun;ZHANG Bang-ning

2009, 27(1): 24-28 .

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This paper studies capacity of CDMA or FDMA/TDMA for multi-beam geostationary earth orbit (GEO) satellite communication systems. Relation is derived between outage probability of the required SNR and the number
of users support at a given power control error (PCE) level and voice activity factor. An expression of capacity of multi-beam GEO CDMA system is then obtained. Numerical results show that capacity is sensitive to system
parameters such as PCE. Using power and continuous phase modulation (CPM), capacity of FDMA/TDMA system is obtained according to the spectral efficiency of CPM. Comparison between CDMA and FDMA/TDMA shows that
capacity of FDMA/TDMA system is larger than CDMA in multi-beam GEO systems.

Fast Stereo Video Encoding Based on AVS

WANG Chong ZHAO Li;LUO Lin

2009, 27(1): 29-33 .

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A new method for fast stereo video encoding based on AVS is presented. In the system, the left-view sequence is encoded by an AVS encoder. For the right-view sequence, combined predictions from the temporal or disparity domains are exploited, with a hierarchical two-stage neural classifier for fast mode decision. The first stage produces different candidates for variable block partitions of each macro-block (MB). The second stage chooses the most suitable prediction sources between forward motion and disparity frames. An improved sum-of-absolutedifferences (SAD) algorithm is proposed in disparity estimation. Experimental results show that the proposed method can achieve time savings up to 80% with negligible quality degradation, and bit-rate increase of only 7%.

Face Feature Extraction and Face Recognition Using Curvelet Transform

NI Xue;LI Qing-wu;MENG Fan;CAI Yan-mei

2009, 27(1): 34-38 .

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As the wavelet transform cannot well express curve characteristics of face image, we propose a feature extraction and face recognition method based on curvelet transform. The face image is first decomposed with curvelets.
Low frequency coefficients are compressed to reduce dimension of feature vectors, and curvelet energy features are calculated in each high frequency subband. The reduced vectors are used to represent features of the face image. Features are then classified using support vector machine. Experimental results on Orl and Yale face databases show that the proposed method is superior to wavelet methods. It is robust to varying illumination conditions, face poses and expressions.

Multi-view Video Coding with View Scalability Based on Correlation Analysis

YAN Tao;AN Ping SHEN Li-quan ZHANG Zhao-yang WANG He

2009, 27(1): 39-43 .

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To display video on a multitude of different terminals, a multi-view coding scheme with view scalability (SMVC) is proposed. Based on a correlation analysis, all views are divided into two groups: base view and enhancement
views. The proposed SMVC adjusts characteristics of various multi-view videos. Experimental results show that the scheme can improve coding efficiency and random access capability.

Progressive Image Transmission for Lossless Images Using
Prior Bitmap

Chin-chen CHANG Pei-yu LIN;Jun-chou CHUANG

2009, 27(1): 44-50 .

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In this paper, we describe a progressive-image-transmission (PIT) scheme based on block-based PIT for lossless images. It is inspired by a previous PIT method presented by Chang et al. Because the original method does not take the significance of each block into consideration, the quality in early stages of decoding is not desirable.To improve it, we propose an enhanced scheme in which a prior bitmap was used to indicate the complexity of each
block. Based on the prior bitmap, significant information of an image can be transmitted to receiver(s) in early stages of transmission. Experimental results show that the proposed scheme can achieve better results both in PSNR values and in visual quality than other former lossless PIT schemes.

Generalized Running Coding with Prime Base for Efficient Steganographic Embedding

ZHANG Xin-peng;WANG Shuo-zhong

2009, 27(1): 51-55 .

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Steganographic coding such as the running coding described in a previous work can be used to improve embedding efficiency, thus enhance steganographic security. In this paper, we modify the original running coding
method and propose a generalized scheme with a prime base. With the generalized approach, each secret digit in a notational system using a prime base is represented by a series of cover values. Alteration to one cover value is used to embed several secret digits so that distortion is significantly reduced. The previous running coding is in effect a special case of the generalized scheme with a prime base p = 2, i.e., the binary system. Theoretical analysis indicates that the generalized running coding with p = 3 provides the best performance.

Application of Multi-granularity Color Features in Image Retrieval

XU Xiang-li;ZHANG Li-biao;YU Zhe-zhou;ZHOU Chun-guang

2009, 27(1): 56-61 .

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As the theory of quotient space granularity comput is imported in image retrieval, a novel image retrieval method using multi-granularity color features is proposed. According to different behaviors under different granularities, one can first obtain color features under different granularities, obtaining different quotient spaces. Second, the obtained quotient spaces are combined based on the quotient space granularity combination principle to achieve image retrieval. Compared with other methods using a single color feature, the image retrieval method based on multi-granularity color features utilizes the image’s own information more effectively. Experimental results demonstrate feasibility and validity of the proposed method.

Classification of Animal Fibers Based on Microscopic Images

SHI Xian-jun;YU Wei-dong

2009, 27(1): 62-66 .

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Scale and pattern of cashmere and fine wool are different, which is used as a major reference to distinguish them. A commonly used technique is to analyze cuticle scale edge height (CSH) of fiber from SEM images. However,
it is expensive and has an average error of 8%. A new method is presented in this paper. After the fiber images are captured with a CCD camera, they are transformed into skeletonzied binary images which are only one pixel
wide and can show fiber and scale edge details. Four relative shape parameters of the fiber scale are extracted. A multi-parameter Bayes classification model is then developed. Numerical experiment results show that, by using an ordinary microscopy, the proposed Bayes model has the performance similar to that based on a scanning electronic microscopy in differentiating cashmere and fine wool (70 S), with accuracy rate approaching 90%.

Lossless Memory Compression and Efficient Frame Storage Architecture for HDTV Video Decoder

GAO Hong-li QIAO Fei YANG Hua-zhong;

2009, 27(1): 67-74 .

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In this work, two schemes are proposed to improve the memory performance in video decoder systems. A novel lossless frame recompression method and an efficient frame storage mapping strategy are employed to reduce the Read/Write and Row Activation operations of the external memory during video decoding processes. Verified with MPEG-2 based HDTV video decoder, the number of bytes writing to the memory is reduced by about 50% in comparison with the conventional decoder using the embedded frame recompression algorithm, without video quality degradation. Moreover, the reading bytes from off-chip memory for motion compensation are not increased. Additionally, by storing the luma and chroma components of one macroblock in one row of different banks, as well as the ten neighboring macroblocks, the logic Row Activation number can be cut down to nearly 5% of the conventional linear storage scheme.

Nonlinear Regularization for Bi-level Image Restoration

ZHANG Jian-jun;WANG Qin

2009, 27(1): 74-78 .

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Restoration of bi-level images is generally performed in two steps, i.e., restoration and thresholding segmentation, which generally does not produce ideal results. This paper proposes a nonlinear regularization method for bi-level image restoration by explicitly using the knowledge of the bi-level image. Unlike the Tikhonov regularization method which eventually results in a linear system of equations, the proposed method leads to a nonlinear optimization problem, solved with the global Barzilai and Borwein gradient method. Simulation results show feasibility and effectiveness of the method.

Application of Fuzzy-Neural Network to Short-Term Forecast of Electric Power Load

HU Yue-li;JI Hui-jie

2009, 27(1): 79-83 .

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Power load forecast is important in energy management with great influence on operation, controlling and planning of electric power systems. Accurate short-term forecast in electric power load can result in cost saving and better operation conditions. Taking into account the complication and uncertainty of short-term load prediction, this paper proposes a short-term load forecast method using fuzzy-neural network (FNN). The FNN model inherits the strong learning ability of neural networks, and has the capability of fuzzy logic for mapping nonlinear functions and extracting similarity from huge historical data. Experiment results show effectiveness of the proposed FNN model. It is applicable to short-term load forecast in power systems with improved performances.

Cost Optimized Reachability with Probability Bound in Priced Probabilistic Timed Automata

ZHANG Jun-hua;HUANG Zhi-qiu;CAO Zi-ning;ZHONG Jing

2009, 27(1): 84-89 .

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This paper solves a reachability problem in priced probabilistic timed automata, which is minimal cost ensuring a probabilistic lower bound. Proper paths that ensure a probability bound in the model are searched. The corresponding priced timed automatons based on these paths are then constructed, and minimal costs obtained. This way, the total minimal cost is naturally obtained. Next, a priced probabilistic timed automaton is extended
to a multi-priced probabilistic timed automaton with multiple price variables. A similar reachability problem in the extended model can also be solved, which is minimal cost on primary cost while ensuring probabilistic lower bound and with respect to secondary cost upper bounds.

Extracting Web Application Models for Model Verification

FANG Ming-ke;MIAO Huai-kou

2009, 27(1): 90-96 .

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For model verification, an approach to extract FSM models of Web applications is proposed. The extraction process is divided into three phases: link extraction, model construction and document generation. By using a regular expression and location technology for tags contained in a tag library built in the lab, information related to links is first extracted from the source codes of Web applications. It is then structured and stored in databases. In model construction, information obtained in the first phase is reconstructed with a mapping and aggregation technology after analyzing elements for model construction such as pages and links within Web applications. Finally, FSM models are obtained to verify the Web applications.

Gaussian Particle Filter in Integrated Navigation System with a Direct Filter Model

ZHOU Zhai-he;LIU Jian-ye;LAI Ji-zhou

2009, 27(1): 97-101 .

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Data fusion of SINS/GPS integrated navigation system is realized using the Gaussian particle filter (GPF) and a direct filtering model. GPF is improved by selecting a suitable important function and a simple algorithmic framework. With parameters of the inertial navigation system (INS) and the GPS pseudo-range, an integrated navigation model is established based on a direct nonlinear filtering method. Implementation is described. Simulation shows that the filtering precision can meet the navigation system’s requirements. Due to the relaxed restriction of the system model and non-Gaussian noise, GPF has advantages in a direct filter system compared to other methods.

Monitoring Aero-engine Gas Path with Electrostatic Sensors

WANG Hua;ZUO Hong-fu;WEN Zhen-hua

2009, 27(1): 102-105 .

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For real time on-line monitoring of components in the gas path of an aero-engine, a gas path condition monitoring method based on electrostatic induction is proposed. The formation mechanism of charged particles in a gas path and the principle of electrostatic sensors are described. Electrostatic sensors are used to monitor the abnormal particles and metal particles in simulation. The result shows that the electrostatic sensor can detect changes in the overall electrostatic charge level due to abnormal particles, indicating availability of the application of electrostatic in gas path monitoring. This provides a basis of developing a technique for airborne aero-engine gas
path monitoring.

Error Calibration for Redundancy Collocation of Six MEMS-IMU

HUANG Hui;LIU Jian-ye;LI Rong-bing

2009, 27(1): 106-110 .

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System calibration techniques are discussed for strap-down redundant inertial measurement units. The measuring principle and calculation formulation are introduced. A new static calibration approach is discussed for non-orthogonal inertial sensor configuration, with which model parameters can be calculated with high precision. The procedure of parameter calculation and the solution is given. Simulation results show that the new approach can improve navigation precision.

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