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Palmprint based identification has attracted much attention in the past decades. In some real-life applications, portable personal authentication systems with high accuracy and speed efficiency are required. This paper presents an embedded palmprint recognition solution based on the multispectral image modality. We first develop an effective recognition algorithm by using partial least squares regression,...
Visual (V) surveillance systems are extensively deployed and becoming the largest source of big data. On the other hand, electronic (E) data also plays an important role in surveillance and its amount increases explosively with the ubiquity of mobile devices. One of the major problems in surveillance is to determine human objects' identities among different surveillance scenes. Traditional way of...
End cutting 1D layout process is a promising candidate for sub-10nm process nodes. To be correctly manufactured, any pair of end cuts must be either merged/aligned or apart from each other with at least a minimum distance. This constraint adversely affects the manufacturability, especially when the end cuts have to be solely printed with the conventional lithography technology. To improve the manufacturability,...
Starting from a set of starting points, the multiple-starting-point optimization searches the local optimums by gradient-guided local search. The global optimum is selected from these local optimums. The region-hit property of the multiple-starting-point optimization makes the multiple-starting-point approach more likely to reach the global optimum. However, for non-smooth objective functions, e.g...
Technology advancements in health care informatics, digitalizing health records, and telemedicine has resulted in rapid growth of health care data. One challenge is how to effectively discover useful and important information out of such massive amount of data through techniques such as data mining. Outlier detection is a typical technique used in many fields to analyze big data. However, for the...
3D printing is revolutionizing the next-generation manufacturing industry. With increasing design complexity, computation in the prefabrication process is becoming the bottleneck of 3D printing. For example, a multi-scale, multi-material 3D design (e.g., a bionic bone) takes a few hours or even days to complete the prefabrication computation. Therefore, it is prudent to improve the performance of...
Community structure of complex network by genetic algorithm has drawn much attention of researchers in various field in recent years. Genetic algorithm is easy to trap into local optimal and also easy to obtain unstable solutions. In order to solve this problem, an effective mutation method combined with node-to-community membership function that is based on the local information of each node in networks...
This paper presents a fast compressive sensing reconstruction algorithm implemented on FPGA using Orthogonal Matching Pursuit (OMP). The algorithm is optimized with QR decomposition to solve the least square problem and avoids the square root operations to facilitate the hardware implementation. The implementation results show that this design can run at a frequency of 100MHz and the proposed algorithm...
Multiple starting point optimization is an efficient approach for automated analog circuit optimization. Starting from a set of starting points, the corresponding local optimums are reached by local optimization method Sequential Quadratic Programming (SQP). The global optimum is then selected from these local optimums. If one starting point is located in a valley, it converges rapidly to the local...
Based on Huygens' principle, the equivalence principle algorithm can decompose a large computational domain into several subdomains and model electromagnetic phenomenon efficiently. This paper analyses the numerical projection error of the equivalence principle operator (EPO), i.e., the error of the scattered equivalent currents on the equivalence surfaces projected from the currents inside the surface...
This paper presents a novel auction-based structure to multi-robot coalition formation problem. The structure, which is called multi-robot Coalition Structure Generation based on Credit Mechanism (CoSGCrM), contains a sub-optimal coalition member selection algorithm with an analysis of its soundness and completeness. A credit mechanism is introduced to reduce the complexity for the coalition leader...
Owning to the advantage of an increase in spectral efficiency by reducing the transmitted pilot tones, compressed sensing has been widely applied to pilot-aided sparse channel estimation in OFDM systems. In this paper, we focus on increasing the accuracy of channel estimation and propose a novel sparse channel estimation method that takes the effect of the additive noise into consideration. In the...
Chemical process industries often suffer from abnormal events of varying magnitudes, which may lead to different consequences, including incipient faults, near-miss, incidents, and accidents. Typically, when an abnormal event occurs, various safety systems, such as alarm systems and safety instrumented systems (SIS), come into play to prevent the event from propagating. To improve process safety,...
This paper describes the blind channel equalization for constant modulus algorithm mathematical model and principle. Focusing on the CMA blind equalization slow convergence and convergence error, the paper analyzes and simulates recent years' constant modulus algorithm and improved algorithm based on residual error and leak CMA nonlinear transformation algorithm. The results show that, compared with...
The K-means algorithm is one of the most well-known clustering algorithms that has been frequently used to variety of problems. However, its processing performance has usually encountered a bottleneck if used to deal with massive data. Since MapReduce as the most popular cloud computing parallel framework is effective to handle massive data, the researches of K-means clustering algorithm which is...
Association rule is one of the key techniques for data mining and knowledge discovery in databases. Before mining association rules from numerical data, however, the variable domains are required to be partitioned into sections first (i.e. the data should be discretized), which will directly affect the quality of association rules to be generated. But it is infeasible to find the best combination...
Discriminant Locality Preserving Projection (DLPP) has been successfully used as a dimensionality reduction technique to many classification problems, which incorporate discriminant information into Locality Preserving Projection (LPP) to improve recognition rate. However, in order to avoid small sample size problem, DLPP needs to reduce dimensions, which will lose some important discriminative information...
For the problems of fundamental frequency changes and the presence of harmonic and interharmonic in microgrid, which bring difficulties to the harmonic analysis of the microgrid, this paper presents a new harmonic and interharmonic analysis method based on cubic spline interpolation algorithm to reconstruct the signal. The simulation results show that the new harmonic and interharmonic analysis method...
The Direct Sequence Spread Spectral (DSSS) communication system has been widely used in military and civilian fields because of its high processing gain, strong ant-jamming and anti-probed capacity, and low intercepted probability. In this paper, an efficient blind parameter estimating and detecting algorithm is proposed, which takes advantage of the autocorrelation property of pseudo random code...
Particle swarm optimization (PSO) is a new stochastic optimization technique based on swarm intelligence. In this paper, we introduce the basic principles of PSO firstly. Then, the research progress on PSO algorithm is summarized in several fields, such as parameter selection and design, population topology, hybrid PSO algorithm etc. Finally, some vital applications and aspects that may be conducted...
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