共查询到20条相似文献，搜索用时 265 毫秒
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文章对包括BF算法,KMP算法,BM算法,BMH算法,AC算法,AC-BM等算法在内的单模式匹配和多模式匹配算法的特点及其复杂度等方面进行了研究。 相似文献
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空域复用多输入多输出(MIMO)系统的接收算法主要有线性接收算法(如ZF算法和MMSE算法)和非线性算法(如ML算法)两大类。其中,线性接收算法复杂性低,需要的计算量少,但是性能较差;ML算法性能较好,但是复杂度高,计算量大。因此需要寻找一种在复杂度和性能之间达到平衡的接收算法。球译码算法作为一种次优的ML算法可以较好的实现复杂度和性能间的平衡,是近年来多输入多输出(MIMO)系统译码算法中的研究热点。介绍了球译码算法的基本原理。 相似文献
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决策树算法是数据挖掘领域的核心分类算法之一,ID3算法则是最为经典的决策树算法。本文以ID3数据挖掘算法在债务管理中的应用为例,验证了算法的性能。 相似文献
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较为系统的综述了当前空间聚类算法的相关研究。依据这些算法的特点,将它们归纳为两类：划分聚类算法、层次聚类算法。针对划分聚类算法,重点分析了PAM、CLARA和CLARANS算法。针对层次聚类算法,重点分析了BIRCH、CURE算法。比较了这些算法的复杂度,并介绍了相关应用。 相似文献
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[目的/意义]算法风险治理是国家总体安全观的重要组成部分,基于主体感知视角识别算法风险结构及关联,能够为算法风险的防范治理提供参考借鉴。[方法/过程]基于感知风险理论,结合902份深度访谈和微博评论混合数据,扎根构建社交平台用户感知算法风险结构模型,并对其关联性展开贝叶斯复杂网络分析。[结果/结论]感知算法风险涵盖算法自身技术风险和算法外延社会风险两个维度8类风险,其中,算法操纵风险是感知算法风险的核心维度,算法共谋风险和算法黑箱风险、算法致瘾风险的关联关系最紧密;信息质量缺陷和行为操纵是关键节点,算法操纵风险以行为操纵为主;社交平台算法应用中存在“算法悖论”现象,即用户算法认知与算法态度间存在背离。该研究完善了现有算法风险理论框架。 相似文献
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文章分析了随即函数模型算法、最小二乘滤波算法、交流采样开平方算法、全波傅氏算法、半波傅氏算法等几种典型的微机保护算法,并论证各种算法的优缺点。通过比较分析,找出符合现代微机保护技术的发展趋势的更快、更准的算法,并为新算法的研究提供现有的理论基础。 相似文献
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提出了一种改进的基因表达式编程算法,将这种算法和传统的基因表达式编程算法进行了对比。算法中设计了种群约简和种群更新两个算子,来提高种群多样性进而改进传统GEP算法的性能。实验显示改进的算法优于传统算法。 相似文献
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针对目前的光照效果实现算法在三维室内设计中无法达到很好的效果的问题,本文提出一种基于多算法融合的三维室内设计光照效果实现算法,该算法首先基于光线跟踪算法进行面片求交优化、球面求交优化和长方体面求交优化,然后再将优化算法及光照阴影算法同时应用于三维室内设计光照效果的实现中。仿真试验结果表明,基于多算法融合的三维室内设计光照效果实现算法相比较现有的算法,对于三维室内设计光照效果的实现更为理想。 相似文献
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O.A. Stepanov V.A. Vasiliev A.B. Toropov A.V. Loparev М.V. Basin 《Journal of The Franklin Institute》2019,356(10):5573-5591
A filtering algorithm is presented for discrete-time linear stochastic systems with polynomial measurements. The techniques to evaluate its efficiency are proposed. The algorithm performance is demonstrated by solving two navigation data processing problems, map-aided navigation using geophysical fields and single-beacon navigation for an autonomous underwater vehicle. The designed polynomial filter is compared to the extended Kalman filter, which is commonly used in practice. The simulation results reveal advantages of the polynomial algorithm. The obtained conclusions are reported. 相似文献
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Since Proportional?+?Integral?+?Derivative (PID) controller is still the workhorse in taking over the workload of process control systems, this article introduces a new design methodology toward improving the performance of such controller. After a PI control law with windup protection is given, it is combined with a derivative path employing a first-order low pass filter in an innovative way to develop a performant controller called PI?+?DF controller. In attempting to attain a high level of control performance, gains of this controller including proportional, integral, derivative and filter gains are tuned choosing the recently introduced Stochastic Fractal Search (SFS) algorithm owing to its superiority to many state-of-the-art algorithms considering convergence, accuracy and robustness. To evaluate the efficacy of SFS, Particle Swarm Optimization (PSO) is also applied to the case study. Furthermore, the presented SFS optimized PI?+?DF controller is compared to a recently reported control scheme through simulation and experimental tests on an identical DC servo system. After providing the stability proof, SFS tuned PI?+?DF controller is found to be the pioneer in exhibiting the most accurate speed response profile under complicated scenarios, which is followed by PSO tuned PI?+?DF controller and the existing control approach, respectively. 相似文献
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《Journal of The Franklin Institute》2021,358(13):6897-6921
This paper presents a novel switching predefined-time parameter identification algorithm with a relaxed excitation condition based on the dynamic regressor extension and mixing (DREM) method. DREM often requires the persistent excitation (PE) of the extended square regressor's determinant to ensure exponential parameter convergence. Unlike the classical DREM method, a new parameter identification algorithm configured with a two-layer filter technique is proposed under a relaxed initial excitation (IE) condition, rather than strict PE. A key point in choosing IE instead of PE is the introduction of a smooth switching function that dominates the pure integral action and filter behavior of the extended square regressor. The proposed algorithm relies on the predefined-time stability theorem and the settling-time of the identification algorithm is set a priori as a system parameter. The contributions of this paper are a novel switching predefined-time parameter estimation algorithm that 1) relaxes the stringent PE condition, 2) achieves predefined-time convergence, and 3) guarantees the monotonicity of each element of the parameter error inherited from the classical DREM method. Comparative simulation results are presented to illustrate the effectiveness of the proposed algorithm. 相似文献
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《Journal of The Franklin Institute》2022,359(6):2737-2754
The robust fault estimation problem for linear discrete time-varying (LDTV) systems subject to multiplicative noise is investigated by means of finite impulse response (FIR) filter. A novel analytical redundancy, expressed via all states of the previous time window, is originally established to construct the fault estimator. To ensure the satisfactory fault estimation accuracy in stochastic sense under the interference of random uncertainty, a new performance index in forms of matrix trace function is proposed. An easy-to-check necessary and sufficient condition is presented to obtain the optimal filter gain via minimizing the performance index at each time instant. It is analytically demonstrated that, the newly proposed fault estimation algorithm enjoys obvious computational advantages in updating the filter gain, especially as the length of the time window increases for time-varying systems. Simulation results are finally provided to verify its feasibility and superiority. 相似文献
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音频信息隐藏技术是一种有效的数字版权保护和信息安全技术。在介绍基于DCT的音频信息隐藏原理的基础上,借助MATLAB软件,利用设计的低通滤波器进而获取信息隐藏载体的音频低频部分,再将欲隐藏的信息替换掉载体音频的低频部分的奇数段中的DCT系数,进而实现音频信息的隐藏,最后还原了被隐藏的信息,证明了算法的可行性。 相似文献
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This paper considers the identification problem of bilinear systems with measurement noise in the form of the moving average model. In particular, we present an interactive estimation algorithm for unmeasurable states and parameters based on the hierarchical identification principle. For unknown states, we formulate a novel bilinear state observer from input-output measurements using the Kalman filter. Then a bilinear state observer based multi-innovation extended stochastic gradient (BSO-MI-ESG) algorithm is proposed to estimate the unknown system parameters. A linear filter is utilized to improve the parameter estimation accuracy and a filtering based BSO-MI-ESG algorithm is presented using the data filtering technique. In the numerical example, we illustrate the effectiveness of the proposed identification methods. 相似文献
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This technical note is concerned with particle filter for the discrete-time nonlinear networked control system. First, modified particle filter algorithm with Markovian packet dropout and time delay is proposed, and its error covariance is benchmarked by Markovian Cramér-Rao lower bound. Second, an upper bound of the Markovian Cramér-Rao lower bound is presented for some special nonlinear networked systems. Third, some necessary conditions for the boundness of error covariance are given by obtaining some sufficient conditions for the bounded Markovian Cramér-Rao lower bound. Finally, numerical examples are presented to illustrate the efficiency of proposed particle filter. 相似文献
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A new design method based on artificial bee colony algorithm for digital IIR filters 总被引：11，自引：0，他引：11
Nurhan Karaboga Author Vitae 《Journal of The Franklin Institute》2009,346(4):328-348
Digital filters can be broadly classified into two groups: recursive (infinite impulse response (IIR)) and non-recursive (finite impulse response (FIR)). An IIR filter can provide a much better performance than the FIR filter having the same number of coefficients. However, IIR filters might have a multi-modal error surface. Therefore, a reliable design method proposed for IIR filters must be based on a global search procedure. Artificial bee colony (ABC) algorithm has been recently introduced for global optimization. The ABC algorithm simulating the intelligent foraging behaviour of honey bee swarm is a simple, robust, and very flexible algorithm. In this work, a new method based on ABC algorithm for designing digital IIR filters is described and its performance is compared with that of a conventional optimization algorithm (LSQ-nonlin) and particle swarm optimization (PSO) algorithm. 相似文献
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结合小波技术对传统的维纳滤波算法进行改进,对语音信号进行离散小波变换,求得小波系数,计算小波系数的阈值,然后利用阈值对小波系数进行过滤,再对小波重构信号,信号经过维纳滤波器模型达到去噪效果。最后对算法进行了仿真试验。 相似文献