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[AI-NN-PR] sade DL : 0: 它是一个基于遗传算法的优化方法，使用微分运算符。它用于解决带有大量未知事物的优化问题。-it is based on a genetic algorithm optimization method, the use of Differential Operators. It used to solve a large number of unknown things with the optimization problem.
Date : 2025-12-29 Size : 2kb User : 苏明春
[AI-NN-PR] 复件 match DL : 0: 心电数据的匹配，对数据中出现的情况分为三类进行匹配，正常，不正常，和未知，对不正常的数据进一步分析-ECG data matching, the data is divided into the three types of matches, normal, abnormal, and unknown to normal data for further analysis
Date : 2025-12-29 Size : 3kb User : 唐娜
[AI-NN-PR] mbclust DL : 0: 基于模型聚类算法的matlab实现 This does the entire MB Clustering given a set of data. It only does the 4 basic models, unequal-unknown priors. It returns the BESTMODEL based on the highest BIC.-model-based clustering algorithm to achieve the Matlab This does the entire MB Clustering given a set of data. It only does the 4 basic models, unequal-unknown priors. It returns the BESTMO DEL based on the highest BIC.
Date : 2025-12-29 Size : 3kb User : 黄风
[AI-NN-PR] AdaptiveLineEnhancer DL : 1: This demonstration illustrates the application of adaptive filters to signal separation using a structure called an adaptive line enhancer (ALE). In adaptive line enhancement, a measured signal x(n) contains two signals, an unknown signal of interest v(n), and a nearly-periodic noise signal eta(n). The goal is to remove the noise signal from the measured signal to obtain the signal of interest.
Date : 2025-12-29 Size : 114kb User : zqq
[AI-NN-PR] 200806 DL : 0: 动态未知环境下移动机器人路径规划遗传算法-Dynamic unknown environment for mobile robot path planning genetic algorithm
Date : 2025-12-29 Size : 1.98mb User : sulei
[AI-NN-PR] tca1_0.tar DL : 0: The tca package is a Matlab program that implements the tree-dependent component analysis (TCA) algorithms that extends the independent component analysis (ICA), where instead of looking for a linear transform that makes the data components independent, we are looking for components that can be best fitted in a tree structured graphical model. The TCA model can be applied in any situation where the data can be assumed to have been transformed by an unknown linear transformation.
Date : 2025-12-29 Size : 222kb User : 薛耀斌
[AI-NN-PR] wangluo DL : 0: 运用神经网络的方法先将数据分类分析,然后再将未知类归类-The use of neural network analysis of data classification methods first, and then classify the unknown category
Date : 2025-12-29 Size : 5kb User : qlovey
[AI-NN-PR] position DL : 0: 基于单目手眼相机和激光测距仪，提出了一种尺寸未知的空间矩形平面的位姿测量算法。该算法不需要知道矩形平面的G 个顶点的物体坐标，只需要知道它们的图像坐标、激光点的图像坐标和激光测距结果，就能够计算出尺寸未知空间矩形平面在相机坐标系下的位姿，并且计算出矩形平面的尺寸。通过建立单目手眼相机和激光测距仪的数学模型，对该算法进行了验证。实验结果表明，该算法是有效的，可以应用于机器人对空间物体的跟踪、定位以及抓取。-Monocular-based hand-eye cameras and laser range finder, a size of an unknown two-dimensional rectangular space Pose measurement algorithm. The algorithm does not need to know the G flat rectangular object vertex coordinates, they only need to know the image coordinates, image coordinates of laser points and the laser ranging results, we can calculate the size of the unknown space rectangular plane in the camera coordinate system bit posture, and to calculate the size of rectangular plane. Through the establishment of monocular hand-eye cameras and laser range finder of the mathematical model, the algorithm is verified. Experimental results show that the algorithm is effective, can be applied to the robot on the space object tracking, positioning, and crawling.
Date : 2025-12-29 Size : 204kb User : 苏朗朗
[AI-NN-PR] coder DL : 0: 在matlab环境下应用蚁群算法对未知系统进行辨识。-Matlab application environment in the ant colony algorithm to identify the unknown system.
Date : 2025-12-29 Size : 4kb User : 郭凯
[AI-NN-PR] unknownfunc DL : 0: Neural/fuzzy approximator construction basics, via an example unknown function
Date : 2025-12-29 Size : 1kb User : Hossein
[AI-NN-PR] RVM_matlabToolBox DL : 2: 相关向量机(RVM)的matlab源程序，包含快速算法，内含代码使用说明。 RVM采取是与支持向量机相同的函数形式稀疏概率模型，对未知函数进行预测或分类。优点： (1) 不仅仅输出预测目标量的点估计值,还可以输出预测值的分布. (2) 使用更少数量的支持向量,从而显著减少输出目标量预测值的计算时间. (3) RVM不需要估计过多的参数. (4) RVM对是否满足Mercer 定理的核函数没有限制,适应性更好. -Relevance Vector Machine (RVM) of the matlab source code, including the fast algorithm that contains the code instructions. RVM to support vector machines with the same function form of sparse probabilistic model to predict the unknown function, or classification. Advantages: (1) The goal is not only the amount of the output forecast point estimates, but also the distribution of the output forecast. (2) use less number of support vectors, thus significantly reduce the amount of predictive value of the output goal of computing time. (3) RVM does not require too many parameters estimated. (4) RVM on whether to satisfy Mercer' s theorem is no limit on nuclear function, adaptability and better.
Date : 2025-12-29 Size : 154kb User : 何创新
[AI-NN-PR] UnknownEnvironmentBasedonFuzzyNeural DL : 0: ：为提高移动机器人在未知环境下避障行为的成功率，通过对障碍物信息的输人，从控制输出数据中找出避障行为模式，生成相应的模糊逻辑控制规则，并把模糊控制算法引入到神经网络中，使得模糊控制器规则的在线精度和神经网络的学习速度均有较大的提高，使移动机器人具有较为迅速的反应能力，实现机器人连续、快速地避障并最终到达目标．系统仿真证明了模糊神经网络在移动机器人路径选择中的智能性．-To enable the mobile robot in unknown environment obstacle—avoiding behavior of Success，based on the information input of obstacles and from the control of output data to find a obstacle—avoiding behavior model，and To create the fuzzy logic rules，a fuzzy control algorithm is introduced to the neural network，allowing mobile robot more rapid response ability and to achieve a robot， and finally reach the target of obstacle avoidance． system sim ulation proves a fuzzy neural network in mobile robot path choice of intelligence．
Date : 2025-12-29 Size : 284kb User : 王风
[AI-NN-PR] work DL : 0: 它可以运行任意有数据的BP神经网络，可以自行设定神经网络隐层数，输入神经元数，输出神经元数。对于未知规律的数据，特别有效-It can run any of the BP neural network with data, you can set their own hidden layer neural network, the input neurons, output neurons. For unknown random data, particularly effective
Date : 2025-12-29 Size : 22kb User : wsh
[AI-NN-PR] LS-TLS DL : 0: LS和TLS算法原理及其Matlab仿真,未知的参数向量常可以建模成矩阵方程，A和b分别是与观测数据有关的系数矩阵的向量。通过使误差的平方和最小来确定参数估计向量。所求得的估计成为最小二乘估计 -LS and TLS Algorithm and its Matlab simulation, the unknown constant parameter vector into a matrix equation can be modeled, A and b are coefficients and the observed data matrix of the vector. By making the square and the minimum error to determine the parameter estimation vector. The estimates obtained by a least squares estimation
Date : 2025-12-29 Size : 1kb User : 云卷云舒
[AI-NN-PR] m DL : 0: 利用行消去法对方程系数行列式进行变换，得到简化行列式，再进行求解-a simple programm only to three unknown quantity
Date : 2025-12-29 Size : 1kb User : 吴用
[AI-NN-PR] 1 DL : 0: 复杂未知环境下机器人路径规划算法研究，复杂未知环境下机器人路径规划算法研究-Complex unknown environment for robot path planning algorithm
Date : 2025-12-29 Size : 4.36mb User : jack
[AI-NN-PR] SVRMHC_download DL : 0: 用此程序预测未知的肽段是否是mhc结合肽-unknown peptides were predicted to be MHC binding peptide by this program .
Date : 2025-12-29 Size : 48kb User : 丛书宁
[AI-NN-PR] Main DL : 0: 基于模型诊断的方法，是根据系统模型，来诊断出故障部件。然而，在很多情况下系统模型是未知的，此时需要通过试验，得到系统的部分模型。执行这些试验需要花费大量的资源和时间，因此针对如何缩减试验的次数，利用基于模型诊断求解的思想提出了几个算法来进行部分模型的识别，实验结果验证了本文方法的有效性。-Model-based diagnostic approach is based on system model, to diagnose the failed component. However, in many cases the system model is unknown at this time through testing, to be part of the system model. Perform these tests need to spend a lot of resources and time, so how to reduce the number of trials for the use of model-based diagnosis solving thinking of a few parts of the model algorithm to the identification, experimental results verify the validity of this method.
Date : 2025-12-29 Size : 2kb User : peizhi
[AI-NN-PR] yichuansuanfa DL : 0: 遗传算法优化问题，对于二个未知数就最值，遗传算法可以通过迭代求出全局最优解。-Genetic algorithm optimization, on the most value for the two unknown, genetic algorithm can find global optimal solution through iteration.
Date : 2025-12-29 Size : 4kb User :
[AI-NN-PR] IrisDC06 DL : 0: 分类是数据挖掘、机器学习和模式识别中一个重要的研究领域。分类的目的是学会一个分类模型 (称作分类器)，该模型能把未知类别的数据项映射到给定类别中。目前发展较成熟的几种分类算法如决策树、神经网络、贝叶斯方法、遗传算法等。分类具有广泛的应用，例如医学诊断、信用卡系统的信用分级、图像模式识别等。本毕业设计通过使用鸢尾属植物(IRIS)数据集，对当前数据挖掘中具有代表性的优秀分类算法进行分析和比较，总结出了各种算法的特性，为使用者选择算法或研究者改进算法提供了依据。-Classification of data mining, machine learning and pattern recognition is an important area of research. The purpose of classification is to learn a classification model (called classifier), the model can unknown types of data items mapped to a given category. Currently the more mature types of classification algorithms such as decision trees, neural networks, Bayesian methods, genetic algorithms. Classification with a wide range of applications such as medical diagnosis, credit card system, credit rating, image pattern recognition. The graduation project by using the Iris genus (IRIS) data sets, data mining has on the current outstanding representative of the analysis and comparison of classification algorithms, summed up the characteristics of various algorithms for researchers to improve the user selection algorithm or algorithm provided.
Date : 2025-12-29 Size : 567kb User : 江霞

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