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psoyouhuannyj
- 基于粒子群优化的神经网络训练算法研究论文 摘 要: 本文提出了基于连接结构优化的粒子群优化算法(SPSO) 用于神经网络训练,该算法在训练神经网络权 值的同时优化其连接结构,删除冗余连接,使神经网络获得与模式分类问题匹配的信息处理能力. 经SPSO 训练的神经 网络应用于Iris ,Ionosphere 以及Breast cancer 模式分类问题,能够部分消除冗余分类参数及冗余连接结构对分类性能 的影响. 与BP 算法及遗传算法比较,该算法在提高分类误差精度的同时可加快训
f_CIN-2-Bhanot-et-al_163
- Data Perturbation Independent Diagnosis and Validation of Breast Cancer Subtypes Using Clustering and Patterns
BP-neural-network
- BP神经网络 乳腺癌诊断 自动选择最佳神经元个数-BP neural network automatically select the best breast cancer diagnosis the number of neurons
hagness_IEEETAP_03
- 时域波束形成实现早期乳腺肿瘤检测,采用超宽带一阶高斯波-time beamforming for early breast cancer detection by UWB
MITAT-boshi
- 一篇关于乳腺癌早期检测的微波热致成像技术的研究论文，博士论文定稿-An early detection of breast cancer caused by microwave thermal imaging technology, research papers, thesis final
MITAT-xitong
- 一篇关于乳腺癌早期检测的微波热致成像技术的硬件系统研究论文-An early detection of breast cancer caused by microwave thermal imaging technology hardware research papers
MITAT-yuanxing
- 一篇关于乳腺癌早期检测的微波热致成像技术的硬件系统研究论文 -An early detection of breast cancer caused by microwave thermal imaging technology hardware research papers
multisensor-image-data-fusion-based-on-pixel-leve
- medical image fusion in breast cancer.
A-constrained-Modulus-Reconstruction-Technique-fo
- medical image fusion in breast cancer.
initially-study-of-an-asymetric-pet-system-dedica
- Medical Image Fusion in Breast Cancer.
Final_Report
- document for breast cancer detection
09_Yogaraj
- Breast cancer classification using HOS
BBioinfYeastzr
- 乳腺癌分类程序，带有有部分的原始数据，非常好 -Breast cancer classification procedures, raw data, with some very good
GBayesian_Claa
- 使用高斯模型对威斯康辛州大学医学院长期乳腺癌数据进行了贝叶叶斯模式识别。识别率为95以上，可以作为模式识别的重要案例。 -Gaussian model the long-term breast cancer data of the University of Wisconsin School of Medicine the Bayeux Yates pattern recognition. Recognition rate of 95 or more can be used as the p
chapter28
- 支持向量机的分类——基于乳腺组织电阻抗特性的乳腺癌诊断-Support vector machine classification- based on the diagnosis of breast tissue electrical impedance characteristics of breast cancer
EJSR_72_3_04
- Breast cancer is the second most common cause of cancer death in women. Early detection is the only way to reduce the mortality. Mammography is the best available technique used for earlier detection. But due to manual reading the performance of
LVQ
- LVQ神经网络的分类——乳腺肿瘤诊断，判定良性还是恶性-LVQ neural network classification- diagnosis of breast cancer
LVQ-BP
- matlab的神经网络算法——解决乳腺肿瘤诊断问题，分别采用BP算法解决以及LVQ算法解决，包含样例乳腺肿瘤数据。-matlab neural network algorithm- to solve the problem of diagnosis of breast cancer, respectively, with BP algorithm to solve LVQ algorithm to solve, contains a sample of breast tumor data.
som_breast
- It diagnoses the breast cancer using som algorithm.
antenna book
- antenna paper for breast cancer detection