Description: 论文标题:自适应模糊系统在手写体数字识别中的应用研究
作者:张镭
作者专业:计算机软件人工智能
导师姓名:黄战
授予学位:硕士
授予单位:暨南大学
授予学位时间:19990501
论文页数:59页
文摘语种:中文文摘
分类号:TP18 TP391.4
关键词:手写体数字 自适应 模糊逻辑 神经网络 模式识别
摘要:该文针对模式识别的特点,构造了适合于模式识别问题的自适应模糊系统,对三种不同学习算法加以改进,在手写全数字识别上对分类器进行了实现,并与采用BP算法训练的三层前馈神经网络分类器相比较,分析其优劣.仿真实验表明,在该文的样本集条件下,自适应模糊分类吕的识别性能优于神经网络分类器,这充分体现了自适应模糊技术用于数字识别的优越性和潜力.-thesis entitled : adaptive fuzzy system in a handwritten numeral recognition of applied research Author : Zhang Lei professional author : artificial intelligence computer software instructor Name : Huang war conferred degrees : Master award units : Jinan University conferred degrees : 19990501 page thesis : Abstracts 59 languages : Chinese Digest Key words : TP18-image Keywords : handwritten digital adaptive fuzzy logic neural network pattern recognition Abstract : In this paper the characteristics of pattern recognition, suitable for the construction of adaptive pattern recognition fuzzy systems, three different learning algorithm to improve the handwriting recognition on digital classification of the device to achieve, BP and with a three-tiered training algorithm for neural network clas Platform: |
Size: 4194405 |
Author:成东 |
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Description: 论文标题:自适应模糊系统在手写体数字识别中的应用研究
作者:张镭
作者专业:计算机软件人工智能
导师姓名:黄战
授予学位:硕士
授予单位:暨南大学
授予学位时间:19990501
论文页数:59页
文摘语种:中文文摘
分类号:TP18 TP391.4
关键词:手写体数字 自适应 模糊逻辑 神经网络 模式识别
摘要:该文针对模式识别的特点,构造了适合于模式识别问题的自适应模糊系统,对三种不同学习算法加以改进,在手写全数字识别上对分类器进行了实现,并与采用BP算法训练的三层前馈神经网络分类器相比较,分析其优劣.仿真实验表明,在该文的样本集条件下,自适应模糊分类吕的识别性能优于神经网络分类器,这充分体现了自适应模糊技术用于数字识别的优越性和潜力.-thesis entitled : adaptive fuzzy system in a handwritten numeral recognition of applied research Author : Zhang Lei professional author : artificial intelligence computer software instructor Name : Huang war conferred degrees : Master award units : Jinan University conferred degrees : 19990501 page thesis : Abstracts 59 languages : Chinese Digest Key words : TP18-image Keywords : handwritten digital adaptive fuzzy logic neural network pattern recognition Abstract : In this paper the characteristics of pattern recognition, suitable for the construction of adaptive pattern recognition fuzzy systems, three different learning algorithm to improve the handwriting recognition on digital classification of the device to achieve, BP and with a three-tiered training algorithm for neural network clas Platform: |
Size: 4194304 |
Author:成东 |
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Description: 利用BP神经网络进行图像分割。主要适用于RGB信息丰富的图像。以RGB为BP网络的三个输入，与对应的灰度图对网络进行训练。-The use of BP neural network image segmentation. RGB is mainly applied to information-rich images. BP network to RGB for the three inputs, with grayscale corresponds to the network training. Platform: |
Size: 24576 |
Author:血狼 |
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Description: 《MATLAB图形技术_绘图及图形用户接口》
MATLAB语言在数值计算，数据处理，自动控制，信号处理，神经网络，优化计算，模糊逻辑，小波分析，图像处理，统计分析等众多领域有着广泛的用途。-" MATLAB graphics _ graphics and graphical user interface" MATLAB language in the numerical calculation, data processing, automatic control, signal processing, neural network, optimization of computing, fuzzy logic, wavelet analysis, image processing, statistical analysis and many other fields have a wide range of applications . Platform: |
Size: 7756800 |
Author:yzy |
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Description: 形态学腐蚀，基于模糊逻辑的形态学灰度算法，用于对图像进行腐蚀运算，可选用多个模糊逻辑算子。参数可调。-Corrosion morphology, grayscale morphology based on fuzzy logic algorithm for computing the image to corrosion, may choose multiple fuzzy logic operators. Adjustable parameters. Platform: |
Size: 2048 |
Author:Mr. Yang |
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Description: 针对合成孔径雷达(SAR) 图像含有大量斑点噪声的特点,基于Contourlet 的多尺度、局部化、方向性和各向
异性等优点,并结合隐马尔科夫树( HMT) 模型和隐马尔科夫场(MRF) ,提出了一种基于Contourlet 域持续性和聚
集性的SAR 图像模糊融合分割算法。该算法有效捕获了Contourlet 子带的持续性和聚集性,并分别用HMT 和
MRF 来刻画,再依据模糊测度,将多尺度HMT 和MRF 有机融合,建立Contourlet 域HMT2MRF 融合模型,并导
出新模型下的最大后验概率(MAP) 分割公式。对实测SAR 图像进行了仿真,仿真结果和分析表明:与小波域上的
HMT2MRF 融合分割及Contourlet 域上HMT 和MRF 分割算法相比,该算法在抑制斑点噪声的同时,有效地提高
了SAR 图像的分割精度- In view of the speckle noise in the synthetic aperture radar (SAR) images , and based on the Contourlet′s
advantages of multiscale , localization , directionality , and anisot ropy , a new SAR image fusion segmentation
algorithm based on the pe rsis tence and clustering in the Contourlet domain is p roposed. The algorithm captures the
pe rsis tence and clus tering of the Contourlet t ransform , which is modeled by hidden Markov t ree (HMT) and Markov
random field (MRF) , respectively. Then , these two models are fused by fuzzy logic , resulting in a Contourlet
domain HMT2MRF fusion model . Finally , the maximum a poste rior (MAP) segmentation equation for the new fusion
model is deduced. The algorithm is used to emulate the real SAR images . Simulation results and analysis indicate that
the p roposed algorithm effectively reduces the influence of multiplicative speckle noise , imp roves the segmentation
accuracy and p rovides a bet te r visual quality for SAR images ove r the Platform: |
Size: 897024 |
Author:周二牛 |
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Description: 模糊算法具有很强的数学逻辑性，将其用于图像处理中图像增强的研究-Fuzzy algorithm has a strong mathematical logic, to image enhancement for image processing research Platform: |
Size: 2048 |
Author:DD |
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Description: 提出了一种基于小波变换和模糊集的图像融合算法.其基本思想是: 首先对图像进行小波变换,获得图
像的低频和高频分量 随后在融合过程中, 对低频和高频分量采取不同的融合策略, 即对低频分量采用平均能
量法进行融合,对高频成分利用图像的模糊集, 寻求一个模糊隶属函数作为融合算子进行融合 最后再对融合
后的图像进行小波反变换,重构出融合后的图像.实验结果证明了方法的有效性.-Proposed image fusion algorithm based on wavelet transform and fuzzy sets. The basic idea is: First the image wavelet transform to obtain the low and high frequency components of the image followed by low and high frequency components in the fusion process to take a different the integration of strategy, integration of the low frequency components using the average energy method, the use of high frequency components of the image fuzzy sets, look for a fuzzy membership function as a fusion operator for fusion image fusion wavelet transform and re- structure of fused images. experimental results demonstrate the effectiveness of the method. Platform: |
Size: 134144 |
Author:张凡 |
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Description: resonance imaging (MRI) data and estimation
of intensity inhomogeneities using fuzzy logic. MRI intensity
inhomogeneities can be attributed to imperfections in the
radio-frequency coils or to problems associated with the acquisition
sequences. The result is a slowly varying shading artifact
over the image that can produce errors with conventional intensity-
based classification. Our algorithm is formulated by modifying
the objective function of the standard fuzzy c-means (FCM) algorithm
to compensate for such inhomogeneities and to allow the labeling
of a pixel (voxel) to be influenced by the labels in its immediate
neighborhood. The neighborhood effect acts as a regularizer
and biases the solution toward piecewise-homogeneous labelings.
Such a regularization is useful in segmenti Platform: |
Size: 227328 |
Author:yangs |
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Search - fuzzy logic for image