复杂背景图像中的车牌检测算法

针对在复杂背景图像中汽车牌照检测定位的课题,提出了一种基于可信度评价的汽车牌照检测定位算法。在对图像进行预处理后,算法利用车牌区域由于字符排列的规则性而在梯度图像上产生的特征,分割并提取出车牌可能存在的候选区域,然后根据汽车牌照的几何特征对每一个候选区域进行可信度评价并按一定的合并规则对候选区域进行合并,以获取更高的可信度,最后根据区域可信度值的大小确定车牌的位置。算法对于图像光照条件变化、视角变化而造成的车牌的倾斜和变形等情况都具有较好的处理效果。     

连续潮流与最优潮流相结合的电力市场双侧竞价交易计划研究

电力市场双侧竟价交易中发电商和用户报价变化所导致的竟价电量波动将会引起电力系统中潮流重新分布，对安全运行产生影响。该文结合双边合同与双侧竞价并计及静态电压稳定裕度约束建立了交易模型，提出将连续潮流和最优潮流相结合，识别双方特定报价水平下网络中存在的薄弱环节，制定出既能实现社会效益最大化，又能保证系统安全运行的交易计划。IEEE30节点系统算例结果表明该文模型和方法的正确性与有效性。     

微带线平行耦合带通滤波器的软件设计

本文介绍了仿真软件ADS在平行耦合带通滤波器设计中的使用。采用ADS对原始电路进行仿真,优化等实现带通滤波器的原始设计,做出了样品,并实验验证了软件设计的合理性和正确性。     

双频三相功率因数校正

文中提出了一种新型的双频三相全桥功率因数校正器拓扑结构。该拓扑结构由两个三相全桥功率因数校正器(PFC)单元级联而成，共用直流母线。其中一个PFC单元工作在高频，决定系统的补偿性能；而另一个工作在低频，主要承担输出功率的任务。该拓扑结构功率因数校正效果与单个高频三相PFC相同，而损耗与单个低频PFC相当。文中对高频PFC单元采用单周控制方式，对低频PFC单元采用滞环控制。仿真和实验结果证实了理论分析的正确性。     

基于COW系统的并行求和算法研究

针对并行求和问题,在Linux环境下组建了一个COW系统,并介绍了在COW系统上的并行求和算法的设计和实现,分析了影响算法性能的因素并提出改进方法,最后给出了并行求和算法在改进前后的实验数据.实验结果表明,当n=2000000时,用改进的算法在两台联想启天4000上测得并行求和效率为80%,而算法改进前在相同的条件下测得并行效率为66.7%,并行效率明显提高.     

Audio-visual sports highlights extraction using Coupled Hidden Markov Models

We present our studies on the application of Coupled Hidden Markov Models(CHMMs) to sports highlights extraction from broadcast video using both audio and video information. First, we generate audio labels using audio classification via Gaussian mixture models, and video labels using quantization of the average motion vector magnitudes. Then, we model sports highlights using discrete-observations CHMMs on audio and video labels classified from a large training set of broadcast sports highlights. Our experimental results on unseen golf and soccer content show that CHMMs outperform Hidden Markov Models(HMMs) trained on audio-only or video-only observations. Next, we study how the coupling between the two single-modality HMMs offers improvement on modelling capability by making refinements on the states of the models. We also show that the number of states optimized in this fashion also gives better classification results than other number of states. We conclude that CHMMs provide a promising tool for information fusion techniques in the sports domain for audio-visual event detection and analysis.     

EFFECTIVE DECENTRALIZED TITO PROCESS IDENTIFICATION FROM CLOSED‐LOOP STEP RESPONSES

In this paper, a new identification method performed in the time domain based on the decentralized step‐test is proposed for two inputs and two outputs (TITO) processes with significant interactions. In terms of parameter identification, the coupled closed‐loop TITO system is decoupled to obtain four individual single open‐loop systems with the same input signal. As in the SISO case, new linear regression equations are derived, from which the parameters of a first‐ or second‐order plus dead‐time model can be obtained directly. The proposed method outperforms the existing estimation methods for multivariable control systems that use step‐test responses. Furthermore, the method is robust in the presence of high levels of measurement noise. Simulation examples are given to show both effectiveness and practicality of the identification method for a wide range of multivariable processes. The usefulness of the identified method in multivariable process modeling and controller design is demonstrated.     

Two-dimensional FLD for face recognition

This paper presents a new scheme of face image feature extraction, namely, the two-dimensional Fisher linear discriminant. Experiments on the ORL and the UMIST face databases show that the new scheme outperforms the PCA and the conventional PCA+FLD schemes, not only in its computational efficiency, but also in its performance for the task of face recognition.     

Slepian-Wolf Coded Nested Lattice Quantization for Wyner-Ziv Coding: High-Rate Performance Analysis and Code Design

Nested lattice quantization provides a practical scheme for Wyner-Ziv coding. This paper examines the high-rate performance of nested lattice quantizers and gives the theoretical performance for general continuous sources. In the quadratic Gaussian case, as the rate increases, we observe an increasing gap between the performance of finite-dimensional nested lattice quantizers and the Wyner-Ziv distortion-rate function. We argue that this is because the boundary gain decreases as the rate of the nested lattice quantizers increases. To increase the boundary gain and ultimately boost the overall performance, a new practical Wyner-Ziv coding scheme called Slepian-Wolf coded nested lattice quantization (SWC-NQ) is proposed, where Slepian-Wolf coding is applied to the quantization indices of the source for the purpose of compression with side information at the decoder. Theoretical analysis shows that for the quadratic Gaussian case and at high rate, SWC-NQ performs the same as conventional entropy-coded lattice quantization with the side information available at both the encoder and the decoder. Furthermore, a nonlinear minimum mean-square error (MSE) estimator is introduced at the decoder, which is theoretically proven to degenerate to the linear minimum MSE estimator at high rate and experimentally shown to outperform the linear estimator at low rate. Practical designs of one- and two-dimensional nested lattice quantizers together with multilevel low-density parity-check (LDPC) codes for Slepian-Wolf coding give performance close to the theoretical limits of SWC-NQ     

On the complexity of and algorithms for finding the shortest path with a disjoint counterpart

Finding a disjoint path pair is an important component in survivable networks. Since the traffic is carried on the active (working) path most of the time, it is useful to find a disjoint path pair such that the length of the shorter path (to be used as the active path) is minimized. In this paper, we first address such a Min-Min problem. We prove that this problem is NP-complete in either single link cost (e.g., dedicated backup bandwidth) or dual link cost (e.g., shared backup bandwidth) networks. In addition, it is NP-hard to obtain a K-approximation to the optimal solution for any K>1. Our proof is extended to another open question regarding the computational complexity of a restricted version of the Min-Sum problem in an undirected network with ordered dual cost links (called the MSOD problem). To solve the Min-Min problem efficiently, we introduce a novel concept called conflicting link set which provides insights into the so-called trap problem, and develop a divide-and-conquer strategy. The result is an effective heuristic for the Min-Min problem called COnflicting Link Exclusion (COLE), which can outperform other approaches in terms of both the optimality and running time. We also apply COLE to the MSOD problem to efficiently provide shared path protection and conduct comprehensive performance evaluation as well as comparison of various schemes for shared path protection. We show that COLE not only processes connection requests much faster than existing integer linear programming (ILP)-based approaches but also achieves a good balance among the active path length, bandwidth efficiency, and recovery time.