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多维函数优化程序
- 用JAVA语言编写，包括PSO（Particle swarm optimization, 中文译名为粒子群优化或微粒群算法), DE (Differential evolution, 中文译名为差分进化或差异演化)等算法，有一些不带约束和带约束的算例（如Michelawicz的几个问题）。使用说明见usage.txt、RUNExample.bat和程序中的注释。 -with Java language, including the PSO (Particle swarm optimizat
peizhun
- 图像配准－GUI界面，最优化算法，互信息尺度，POWELL.m附属子程序，PSO.m附属子程序，对图像进行“平移”和“旋转”-Image Registration - GUI interface, optimization algorithms, mutual information scale, POWELL.m subsidiary subroutine, PSO.m subsidiary subroutine, the right image "translation"
MT-principles-and-methods
- 中科院计算所刘群老师关于机器翻译的课件。-CAS Institute of Computing Qun machine translation of the courseware on the teacher.
VB_GAP_old_C
- 匈牙利法指派，用VB翻译的，可能有些问题，遇到参数一样的指派会会死循环-Assigned to Hungary and France, using VB translation, may be some problems encountered in the same parameters will be assigned to death cycle
finalproject
- Graphics program to draw line , cirlce, rectangler, square, sphere, ellipse, ellipsoide, cone, and make translation, rotation, shearing, scaling
softwarecode
- 中文分词是中文信息处理中的重要环节，中文分词技术广泛应用于自动翻译、文本检索、语音识别、文本校对、人工智能以及搜索引擎技术等领域。中文分词算法的选择，中文词库的构建方式，词库中词条的完备性在很大程度上与中文分词系统性能紧密相关。-Chinese word segmentation in Chinese information processing is an important part of Chinese word segmentation technology is widely used
hanmeng
- 汉语蒙语/机器翻译 /信息检索/ C++ /人工智能-Chinese Mongolian Dictionary/Machine Translation/Information Retrieval/C++/AI
GAforMaxfunction
- 遗传算法求函数极值算是遗传算法的一种最简单的应用，这里就介绍一种简单的，全文基本翻译自codeproject的一篇文章，作者为Luay Al-wesi，软件工程师。例子中的函数为y = -x^2+ 5 ，大家可以将其改为其他复杂一些的函数，比如说f=x+10sin(5x)+7cos(4x)等。本篇文章适合遗传算法初学者阅读，大牛请绕道，呵呵。文后附C语言代码，全部代码在VC6.0上编译通过。 代码中文说明见：http://blog.csdn.net/xujinpeng99/archive/2
neural-network-design-chinese
- 神经网络设计中文版，国内最好的神经网络翻译文-Chinese version of neural network design, the best neural network of domestic Translation
supporting-vector-machine
- 关于支持向量的一些理论知识，是英版的翻译，翻译的还可以。-Some theoretical knowledge on the support vectors, the English version of the translation, and translation.
Robot-athletics-series
- 日本人的关于机电一体化的，至于机器人就看各位的编程水平了，翻译过的-The Japanese on the mechanical and electrical integration, As for the robot see you for the level of programming, translation
gafit
- 联合运用粗糙集(RS)理论-遗传算法(GA)-支持向量机(SVM)方法研究真核生物翻译起始位点(TIS)的识别.-A classification model is built to recognize translation initiation sites (TISs) in eukaryotes by applying rough sets-genetic algorithm-support vector machine (RS-GA-SVM).
Design-and-Implementation-of-a
- 英文电梯文献 可以毕设翻译 很实用的 电梯群控系统的研究 模糊神经网络-English Elevator literature Complete set of very practical translation of the elevator group control system the fuzzy neural network
LS-SVM
- 支持向量机所用工具箱的翻译，是本人亲自翻译的，目前中文版是从这个衍生来得。-Support vector machine translation of the toolbox, I personally translated the Chinese version is derived from this more.
Character_Regonition_ANN
- Character recognition, usually abbreviated to optical characte r recognition or shortened OCR, is the mechanical or electronic translation of images of handwritten, typewritten or printed text (usually captured by a scanner) into machine - edit
natural-language-processing
- 统计自然语言处理PPT-刘挺 中科院自动化研究所、模式识别国家重点实验室的 介绍的内容有统计机器翻译、词法分析与词性标注、语料库与词汇知识库-Statistical Natural Language Processing PPT-Ting Liu Institute of Automation, Chinese Academy of Sciences, State Key Laboratory of Pattern Recognition content presentation of
face
- 通过定位人眼进行人脸切割，该算法进行了修正，同时还具备人脸校正功能，可进行测试照片的旋转和平移。-By positioning the human eye human face cut, the algorithm is modified, also has a face correction function can be tested in photo rotation and translation.
GA-ZHOU
- 周家驹等翻译的这本演化程序，以遗传算法作为基本实现方式，并指出了软件实现的步骤-Zhou Jiaju equivalent translation of this evolution process, genetic algorithm as the basic implementation, and noted that the steps implemented in software
Deep-Learning(UFLDL)
- Stanford大学Andrew Ng的Deep Learning(UFLDL)教程中文翻译合集，原网址：http://deeplearning.stanford.edu/wiki/index.php/UFLDL E6 95 99 E7 A8 8B-Deep Learning(UFLDL)Translation Version(Chinese)
quasi-rnn-master
- A TensorFlow Implementation of Character Level Neural Machine Translation Using the Quasi-R-A TensorFlow Implementation of Character Level Neural Machine Translation Using the Quasi-RNN