基于JPEG2000的码率控制算法的研究

码率控制是JPEG2000编码的重要过程,其算法的优劣直接决定着整个编码效率的高低和压缩图像质量的好坏.针对JPEG2000标准建议的码率控制算法的计算复杂度高且占用存储空间大的问题,提出了对隔行扫描编码通道算法ACPI的一种改进算法,包括添加估计斜率值阶段、逆转扫描分辨率水平顺序,以及逆转同等级子带扫描的顺序.实验结果表明,该算法有效地减少了一JPEG2000的计算复杂度和存储量,提高了性能.     

一种应用遗传算法的彩色图像分割方法

遗传算法在复杂大空间搜索近似最优值有着很好的效果,利用遗传算法的优势,应用其解决图像分割问题.图像分割中,区域间差别度和区域内相似度是评价图像分割的重要因素,用遗传算法优化图像区域间差别和区域内相对相似度,获得高质量的图像分割结果.为了提高算法效率,采用贪心方法进行图像预处理,以及最小生成树初始化来减小算法的规模和搜索空间.实验证明采用遗传算法在图像分割问题可取得有效的结果.     

基于改进惯性权重的粒子群优化算法

惯性权重是粒子群算法中平衡全局搜索和局部搜索能力的重要参数,提出了一种基于改进惯性权重的粒子群优化算法。该算法在进化初期采用基于不同粒子不同维的动态自适应惯性权重策略,加快收敛速度,在进化后期采用线性递减权重策略,同时为防止陷入局优,适时引入混沌变异增加种群多样性。对5个典型测试函数的测试结果表明,NPSO在收敛速度、收敛精度、稳定性和全局搜索能力等方面比线性权重PSO(LDIWPSO)均有很大程度上的提高。     

FPN推理模型在上下文感知系统中的应用研究

研究模糊Petri网模型在上下文感知系统中的快速推理算法.针对模糊Petri网的通用推理算法不能解决“或逻辑”问题,提出了模糊Petri网推理算法从变迁开始搜索,区别于通常从库所开始搜索的策略,有效解决了“或逻辑”问题;并在不增加虚库所和虚变迁的前提下对变迁先排序后再进行推理,降低了算法的空间和时间复杂度.最后,对模糊Petri网模型和推理算法进行仿真,实验结果验证了该算法的有效性.     

支持JSR286和WSRP2.0规范的Portlet协作的设计

JSR286规范定义了本地Portlet之间的协作方式,WSRP2.0规范定义了远程Portlet之间的协作方式,但两者并未深入涉及远程Portlet和本地Portlet之间的协作问题,降低了Portlet的交互能力。针对这点不足,在WSRP2.0规范定义的事件分发及状态分发等协作机制基础上,设计了一个消费者门户主导的联邦协作框架。在该框架中,通过协作信息转换和协作服务作为中介,通过消息队列进行消息存储、消息验证和消息处理,实现了Portlet容器和代理容器的松散耦合,并支持远程Portlet和远程Portlet之间、远程Portlet和本地Portlet之间、本地Portlet和本地Portlet之间的协作。该框架与JSR286规范和WSRP2.0规范兼容,满足WSRP2.0模块的可插拔性,并具有良好的可扩展性和可移植性。     

Corrective classification: Learning from data imperfections with aggressive and diverse classifier ensembling

Learning from imperfect (noisy) information sources is a challenging and reality issue for many data mining applications. Common practices include data quality enhancement by applying data preprocessing techniques or employing robust learning algorithms to avoid developing overly complicated structures that overfit the noise. The essential goal is to reduce noise impact and eventually enhance the learners built from noise-corrupted data. In this paper, we propose a novel corrective classification (C2) design, which incorporates data cleansing, error correction, Bootstrap sampling and classifier ensembling for effective learning from noisy data sources. C2 differs from existing classifier ensembling or robust learning algorithms in two aspects. On one hand, a set of diverse base learners of C2 constituting the ensemble are constructed via a Bootstrap sampling process; on the other hand, C2 further improves each base learner by unifying error detection, correction and data cleansing to reduce noise impact. Being corrective, the classifier ensemble is built from data preprocessed/corrected by the data cleansing and correcting modules. Experimental comparisons demonstrate that C2 is not only more accurate than the learner built from original noisy sources, but also more reliable than Bagging [4] or aggressive classifier ensemble (ACE) [56], which are two degenerated components/variants of C2. The comparisons also indicate that C2 is more stable than Boosting and DECORATE, which are two state-of-the-art ensembling methods. For real-world imperfect information sources (i.e. noisy training and/or test data), C2 is able to deliver more accurate and reliable prediction models than its other peers can offer.     

A hybrid differential evolution algorithm integrated with an ant system and its application

A new hybrid differential evolution algorithm, in which an ant system is used to select the optimal base vector of mutation operation, named the ant system differential evolution (ASDE), is proposed. In ASDE, each dimension in the feasible solution space is divided into several subspaces evenly, and each subspace is marked with the same initial intensity of pheromone trails. The probability of choosing an individual as the base vector is influenced by the visibility and pheromone quantity of the individual. The trail of the selected base vector’s location subspaces will be reinforced with some pheromones, when the offspring is better than its parent. The experimental results show that the ASDE generally outperforms the other differential evolution algorithms for nine benchmark functions. Furthermore, the ASDE is applied to develop the global kinetic model for SO₂ oxidation on the Cs-Rb-V catalyst, and satisfactory results are obtained.     

Positive periodic solutions of neutral predator–prey model with Beddington–DeAngelis functional response

By using a continuation theorem based on coincidence degree theory, some new sufficient conditions are obtained for the existence of positive periodic solutions for a neutral predator–prey model with the Beddington–DeAngelis functional response.     

A robust motion estimation with center-biased diamond search and its parallel architecture for motion-compensated de-interlace

For motion compensated de-interlace, the accuracy and reliability of the motion vectors have a significant impact on the performance of the motion compensated interpolation. In order to improve the robustness of motion vector, a novel motion estimation algorithm with center-biased diamond search and its parallel VLSI architecture are proposed in this paper. Experiments show that it works better than conventional motion estimation algorithms in terms of motion compensation error and robustness, and its architecture overcomes the irregular data flow and achieves high efficiency. It also efficiently reuses data and reduces the control overhead. So, it is highly suitable for HDTV applications.     

Hydrogen sensor based on Pd-functionalized film bulk acoustic resonator

We present an application of the Pd-functionalized film bulk acoustic resonator for hydrogen detection. The resonator consisted of an AlN piezoelectric stack and a Bragg reflector has a working resonance near 2.23 GHz and a high performance. A 50 nm thick Pd film was coated on the top electrode as a specific layer to capture hydrogen. The absorption of hydrogen can trigger changes of elastic properties of the Pd layer, which affects the resonance frequency of the resonator. The experimental results show that the Pd-functionalized film bulk acoustic resonator can yield a rapid, sensitive, reversible and reproducible response to hydrogen in the concentrations from 0.3% to 2%. The advantages of this sensor, including the simple fabrication process, ease of detection method, rapid response and high sensitivity and working at room temperature, make this promising in the early alarm of hydrogen leaking.