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模式识别-神经网络bp算法用于模式分类，采用了matlab自带的接口函数-pattern recognition-bp neural network algorithm for pattern classification, using the Matlab's own interface function
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模式识别，算法用于模式分类，采用了matlab自带的接口函数-pattern recognition algorithm for pattern classification, using the Matlab's own interface function
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This package contains the Matlab codes implementing the ScSPM algorithm described in CVPR 09 paper "Linear Spatial Pyramid Matching using Sparse Coding for Image Classification".
-This package contains the Matlab codes implementing the ScSPM algori
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使用BP神经网络进行的3维样本分类matlab算法-Using BP neural network of three-dimensional sample classification matlab algorithm
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本程序是用Matlab编写的用KNN算法解决文本分类问题的程序。-The program is written in Matlab using KNN algorithm to solve the text classification procedures.
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该程序为matlab程序，共有三个文件，dataC.m为程序入口，实现功能对50组数据用k均值算法进行分类，再对40组数据用感知器算法训练，然后用训练得到的判别函数对剩下10组数据分类，最后与原始分类做差比较，若分类无误，则全显示为0.-Matlab program on the program, a total of three files dataC.m for program entry features 50 sets of data with k-means algorithm to
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支持向量机的matlab商业软件包，附有中文和英文使用手册说明，可以在对算法不了解的基础上，利用简单的命令完成支持向量机的分类和回归建模-Support vector machine (SVM) commercial software package in matlab, accompanied by Chinese and English manual, can be on the basis of the algorithm does not understand, using simple
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MATLAB代码，采用封装法利用K近邻和遗传算法的结合对数据进行分类-MATLAB code using encapsulation method using a K-nearest neighbor and genetic algorithm combined with data classification
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在 Windows 环境中用MATLAB实现LMS学习算法，解决“苹果-橘子”模式分类问题。-Windows environment using the MATLAB realize LMS learning algorithm to solve the " Apple- Orange" pattern classification.
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用BP网络解决XOR分类问题,本次实验主要是让大家对 BP 网络有进一步了解和认识，熟知BP 算法以及其在MATLAB中的程序实现，在掌握这些基本原理的同时解决XOR的分类问题。-XOR using BP network to solve classification problems, mainly of this experiment is to let everyone have a better understanding of BP network and understanding,
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对于初学matlab的同学会有帮助，Relief计算分类权重，基于分段非线性权重值的Pso算法，直线阵采用切比学夫加权控制主旁瓣比，D-S证据理论数据融合，主要是基于mtlab的程序。-Matlab for beginner students will help, Relief computing classification weight, Based on piecewise nonlinear weight value Pso algorithm, Linear array using c
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脉冲响应的相关分析算法并检验，采用热核构造权重，迭代自组织数据分析，可以实现模式识别领域的数据的分类及回归，包括广义互相关函数GCC时延估计，基于SVPWM的三电平逆变的matlab仿真。- Related impulse response analysis algorithm and inspection, Thermonuclear using weighting factors Iterative self-organizing data analysis, You can achieve
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相参脉冲串复调制信号，采用加权网络中节点强度和权重都是幂率分布的模型，课程设计时编写的matlab程序代码，可以实现模式识别领域的数据的分类及回归，是信号处理的基础，部分实现了追踪测速迭代松弛算法。- Complex modulation coherent pulse train signal, Using weighted model nodes in the network strength and weight are power law distribution, Course desi
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matlab编写的元胞自动机，IDW距离反比加权方法，LCMV优化设计阵列处理信号，是信号处理的基础，使用高阶累积量对MPSK信号进行调制识别，Relief计算分类权重，GPS和INS组合导航程序，结合PCA的尺度不变特征变换(SIFT)算法。- matlab prepared cellular automata, IDW inverse distance weighting method, LCMV optimization design array signal processing, Is
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Improved genetic algorithm and fuzzy C- means clustering MATLAB source. The fuzzy C- means algorithm is easy to converge to local minima, in order to overcome the shortcomings of the genetic algorithm is applied to fuzzy C- means algorithm (FCM) opti
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基于matlab的bp神经网络学习算法用于数据的分类--主要针对语音信号进行分类。本案例中选举了民歌、古筝、摇滚和流行音乐四类不同类型，用bp神经网络实现对这四类音乐的有效分类(Based on matlab bp neural network learning algorithm for data classification - mainly for voice signal classification. In this case, four different types of folk
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This Matlab program implements the cochannel speech separation algorithm Yi Jiang, D. L. Wang, et al. (2014), "Binaural Classification for Reverberant Speech Segregation Using Deep
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用MATLAB实现Adaboost分类算法，只是一个简单的功能(Using MATLAB to implement Adaboost classification algorithm, it is just a simple function)
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K-means算法是硬聚类算法，是典型的基于原型的目标函数聚类方法的代表，它是数据点到原型的某种距离作为优化的目标函数，利用函数求极值的方法得到迭代运算的调整规则。K-means算法以欧式距离作为相似度测度，它是求对应某一初始聚类中心向量V最优分类，使得评价指标J最小。算法采用误差平方和准则函数作为聚类准则函数。(The K-means algorithm is a hard clustering algorithm, which is representative of the prototy
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实验示例是基于语音中的mfcc，语音倒谱特征来进行聚类，先利用训练样本来计算训练样本聚类中心（用到了lbg算法），之后再进行分类。
注意：使用代码时需要自己更改文件路径。(This example is based on the MFCC in speech and the feature of speech Cepstrum to cluster. First, the training sample is used to calculate the training sample clus
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