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Description: 利用主成分分析法对BP神经网络的输入参数进行降维，然后进行网络的训练，PCA-BP处理的结果同单一的bp相比，不仅提高了网络的收敛速度，而且提高了网络对预测数据分类的精度
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Size: 1184 |
Author: 娜娜 |
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Description: 经典的人工智能问题 - iris数据分析问题。通过设计三层bp神经网络对花朵数据进行分类识别，并达到了很好的效果。-classic AI problem- iris data analysis problems. Three-bp through the design of neural networks classify data flower identification, and to achieve good results.
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Author: lyx |
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Description: ICA can be used in brain activation studies to reduce the number of dimension and filter out independent and interesting activations. This demonstration shows two studies. One provided by Hvidovre Universitets Hospital, Denmark, that consists of fMRI scannings of humans. Another provided by the EU sponsored MAPAWAMO project from fMRI scannings of monkeys. In the demo comparison between icaMS, icaML, icaMF, icaMF (positive sources) and PCA can be made. More detailes can found in [2].
-ICA can be used in brain activation studies to reduce the number of dimension and filter out independent and interesting activations. This demonstration shows two studies. One provided by Hvidovre Universitets Hospital, Denmark, that consists of fMRI scannings of humans. Another provided by the EU sponsored MAPAWAMO project from fMRI scannings of monkeys. In the demo comparison between icaMS, icaML, icaMF, icaMF (positive sources) and PCA can be made. More detailes can found in [2].
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Author: 海心 |
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Description: 利用主成分分析法对BP神经网络的输入参数进行降维，然后进行网络的训练，PCA-BP处理的结果同单一的bp相比，不仅提高了网络的收敛速度，而且提高了网络对预测数据分类的精度-Using principal component analysis method of BP neural network for dimensionality reduction of input parameters, and then training the network, PCA-BP deal with the results of a single bp, compared with not only improve the network convergence rate, and improve the network prediction data Classification accuracy
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Size: 1024 |
Author: 娜娜 |
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Description: 人脸识别工具箱,包含了PCA,LDA两中方法-Face Recognition toolbox contains PCA, LDA in the two methods
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Size: 59684864 |
Author: fengbin |
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Description: 主分量分析(PCA ) 是统计学中分析数据的一种有效的方法, 可以将数据从高维数据空间变换到低维特征空间, 因而
可以用于数据的特征提取及压缩等方面。在该文的形状识别系统中, 用PCA 法提取图像的形状特征, 能够较好地满足识别
层的输入要求。在识别层研究了3 种识别方法: 最近邻法则、BP 网络及协同神经网络方法, 均取得了满意的实验效果。-Principal component analysis (PCA) is a statistical analysis of data in an effective method to data from high dimensional data space transformation to the low-dimensional feature space, which can be used for data feature extraction and compression and so on. In this paper, the shape recognition system using PCA extraction of the shape of image features, can be used to satisfy the identification requirements of the input layer. In the recognition layer studied three kinds of identification methods: nearest neighbor rule, BP network and the synergetic neural network methods, have achieved a satisfactory experiment results.
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Size: 277504 |
Author: 陈平 |
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Description: BP 图像识别算法，基于pca的方法，外国人写的-BP image recognition algorithm, pca-based approach, written by foreigners
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Size: 9413632 |
Author: qiuyigui |
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Description: 1.BP神经网络进行模式识别
2.用BP网络对非线性系统进行辨识
3.一个神经网络PID控制器
4.图像处理的PCA算法
5.图像处理的穷举算法-1.BP neural network pattern recognition 2. Using BP network identification of nonlinear systems 3. A neural network PID controller 4. The PCA algorithm for image processing 5. The exhaustive algorithm for image processing,
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Size: 5120 |
Author: hudingyin |
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Description: 本文设计基于DCT的人脸识别系统，首先结合当今人脸识别的背景和发展状况讨论了人脸识别的研究内容及在各方面的应用；然后研究了人脸识别进行预处理，讨论了人脸识别预处理的其他方法，分析各种方法的利弊，最后采用DCT（离散余弦变换）实现人脸图像预处理中的降维处理；接下来对人脸图像的特征提取进行了研究，简单叙述了几何特征提取和代数特征提取，同时深入研究了基于DCT和PCA变换的人脸图像特征提取，从而实现是否对人脸识别系统识别率有所提高的研究；对于分类器的选择，本文对两种分类器进行了探讨，即最近邻分类器和BP神经网络分类器，同时采用BP神经网络分类器作为本次基于DCT的人脸识别系统设计的分类器，并对BP神经网络进行分类的算法进行设计，BP神经网络具有学习功能，只要采用本系统对训练图片进行训练，就可以记下图像的相关信息，对于测试图片，就可以很准确的识别出该图片是属于哪个的。最后，本文对整个人脸识别系统设计实验进行了实验分析，实验结果表明本文采用的方法切实有效。- This is the design of the DCT-based face recognition systems. First of all, the background light of the current face recognition and face recognition to discuss the development of research in all aspects of content and applications And then studied the pretreatment of face recognition to discuss the pre-treatment of other face recognition methods,and analysis of the pros and cons of various methods, finally, the use of DCT (discrete cosine transform) image pre-processing to achieve in the face of the reduced-order processing Next on the face image feature extraction have been studied, A brief description of the feature extraction and algebraic geometry feature extraction, while in-depth study based on the DCT and the PCA Transform face image feature extraction in order to achieve face recognition system to identify whether the rate of increase in the research For the choice of classifier, this paper carried out on two of classifier, that is, nearest neighbor classifier and BP neura
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Author: 刘文珍 |
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Description: 基于BP神经网络的人脸识别系统的研究 采用的是PCA和BP网络-Based on BP neural network face recognition system using PCA and BP Neural Network
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Size: 221184 |
Author: 张正峰 |
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Description: PCA+BP神经网络的人脸识别程序已进行仿真，可实现-Face recognition program of the PCA+BP neural network simulation can be realized
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Size: 2048 |
Author: 陈雨轩 |
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Description: BP神经网络训练以及检验，得到结果与设定值的误差，训练数据越多结果会越好。PS:为了获得更好的效果，请先用PCA或线性回归等方法对学习数据进行预处理。-BP neural network training and testing, the results obtained with the set value of the error, the more training data results will be better. PS: In order to obtain better results, please use PCA or linear regression methods such as learning data preprocessing.
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Size: 1024 |
Author: 徐馨珂 |
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Description: 基于BP网人脸识别, 使用PCA方法对人脸特征进行抽取-Face Recognition Based on BP Network
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Size: 355328 |
Author: fangjing |
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Description: 针对稀疏表示识别方法需要大量样本训练过完备字典且特征冗余度较高的问题，提出了结合过完备字典学习与PCA降维的小样本语音情感识别算法.该方法首先用PCA降维方法将特征降维，再将处理后的特征用于过完备字典训练与稀疏表示识别方法，从而给出了语音情感特征的稀疏表示方法，并确定了新算法的具体步骤.为验证其有效性，在同等特征维数下，将方法与BP, SVM进行比较，并对比、分析语音情感特征稀疏化前后对语音情感识别率、时间效率以及空间效率的影响.试验结果表明，所提出方法的识别率比SVM与BP高 与采用稀疏化前的特征相比，稀疏化后的特征向量更便于处理，平均识别率提高约15 ，时间效率提高近原来的1 /2，空间效率提升近原来的1 /3.
-Identification methods for sparse representation requires a lot of training samples and high over-complete dictionary feature redundancy problem, a combination of over-complete dictionary learning and PCA dimension small sample speech emotion recognition algorithms. Firstly, the PCA dimension reduction methods feature reduction, feature and then treatment for the over-complete dictionary training and recognition sparse representation, which gives a speech emotion feature sparse representation, and to determine the specific steps of the new algorithm. To verify its validity, in Under the same number of features, the method and BP, SVM compare and contrast, analyze the impact before and after the speech emotion feature sparse speech emotion recognition rate, time-efficient and space-efficient. experimental results show that the recognition rate of the proposed method than High SVM and BP compared to pre-thinning characteristics using eigenvectors easier after thinning processing, the av
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Size: 629760 |
Author: wangming |
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Description: 基于PCA-BP神经网络的接地网故障诊断算法-Ground Fault diagnosis algorithm PCA-BP neural network
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Size: 304128 |
Author: yanghceng |
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Description: 在建模前先将数据利用PCA进行降维，将降维后的数据作为BP神经网络的输入因子，对数据进行拟合。-Before the first data modeling use PCA dimensionality reduction, the reduced dimensionality of the data as the input factor BP neural network, the data fitting.
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Size: 62464 |
Author: 范振东 |
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Description: 又提供一基于生理的情感神经网络，包含杏仁体，丘脑，视觉神经等重要元素，可用于分类与预测，性能优越于SVM，BP-The use of neural network based on emotional physiology, contains important elements of the amygdala, thalamus, optic nerve, etc., can be used for classification and prediction, superior performance to SVM
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Size: 9177088 |
Author: 稻草人 |
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Description: PCA和BP神经网络结合，适用于人脸识别中-PCA and BP neural network for face recognition
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Size: 4227072 |
Author: 刘伟 |
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Description: The pca method was used for the classification of BP neural network
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Size: 19456 |
Author: 已二一一
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Description: 一种基于改进BP神经网络的PCA人脸识别算法(An improved BP neural network PCA algorithm for face recognition)
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Size: 538624 |
Author: sssh123
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