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d_0609030843321
- 用有限状态机实现的走迷宫演示程序，用到了opengl，可以当作DEMO来用-finite state machine to achieve the Maze demo program, used the opengl, to be used as DEMO
基于有限状态机的汉语数字语音端点检测
- 基于有限状态机的汉语数字语音端点检测.rar.rar格式为ｖｉｐ-based on the finite state machine language digital voice endpoint detection. Rar.rar format vip
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- 有穷状态机，利用VC6.0编写蚂蚁找食的模拟程序-Finite state machine, the use of ants looking for food preparation VC6.0 simulation procedures
InferNet2.3
- Infer.NET is a .NET framework for machine learning. It provides state-of-the-art message-passing algorithms and statistical routines for performing Bayesian inference.
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- FSVM在人眼状态识别中的应用,一种结合gabor滤波和模糊支持向量机进行人眼状态检测的方案-FSVM in the human eye pattern recognition application, a combination of gabor filtering and fuzzy support vector machine is the human eye state inspection programs to
svm-phasestateofcloudclassificationalgorithmsource
- 利用支持向量机的分类特性，结合modis的云图像，对云相态进行分类，利用svm云相态分类算法源代码-The use of support vector machine classification of features, combined with clouds modis images of the cloud phase state classification using svm-phase state of cloud classification algorithm source c
cuSVMVCcode
- 基于GPU计算的SVM，VC++源码，包括详细文档说明文件。借用了GPU编程的优势，该代码据作者说比常规的libsvm等算法包的训练速度快13-73倍，预测速度快22-172倍。希望对大家有用-cuSVM is a software package for high-speed (Gaussian-kernelized) Support Vector Machine training and prediction that exploits the massively parallel proc
lsm
- Liquid State Machine toolbox
zeeland2009
- Reverse-engineering state machine diagrams from legacy C-code
Supportvectormachinebasedbatterymodelforelectricve
- The support vector machine (SVM) is a novel type of learning machine based on statistical learning theory that can map a nonlinear function successfully. As a battery is a nonlinear system, it is difficult to establish the relationship between th
USGate
- 超声闸门处理,以及脉冲状态机的管理维护代码-Ultrasound gate processing, and pulse code state machine management and maintenance
SVM-Multiregression
- SVM Multiregression for Non Linear Channel Estimation in Multiple-Input Multiple-Output Systems 在多输入多输出系统中的SVM多元回归非线性逼近-This paper addresses the problem of Multiple-Input Multiple-Output (MIMO) frequency non-selective channel estimation. We d
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- 针对齿轮箱振动信号的非平稳性和非线性, 提出一种多重分形和支持向量机相结合的故障 诊断方法。运用多重分形理论方法对齿轮振动信号进行分析, 通过分析发现多重分形谱和广义维数作 为故障特征能够很好地反映齿轮箱的工作状态 对支持向量机的参数利用粒子群优化算法进行优化, 并 将齿轮箱振动信号的多重分形特征量作为支持向量机的输入参数以识别齿轮的故障类型。实验结果表明, 该方法在样本较小的情况下能够准确对齿轮箱的故障类型进行分类-Gearbox vibration signal of non-s
StateMachine
- 一个有限状态机的编程范例 StateMachine包 状态机管理 IStateMachine.as 状态机接口 MyEvent_Control.as 消息管理,状态管理 MyEvent_Single.as 单个事件 Total.as 实现了状态机接口(IStateMachine)的基类,将其理解为抽象类比较好 A.as 继承基类(Total)的状态机,这个才是真正可用的 B.as 同A Main.as 调用,以及启动 若要使
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
Boltzmann
- 对一个三节点的玻尔兹曼机，在初始温度和初态确定的情况下，采用步长为-0.1的线性降温方式训练，通过编写程序确定在T 0时的状态-For a three-node Boltzmann machine, in the case of initial temperature and initial state determination, the use of a step-by-step linear cooling mode training, through the preparation of
Programming-Game-AI-by-Examples-
- 《游戏人工智能编程案例精粹》主要讲述如何使游戏中的角色具有智能的技术。本书首先介绍游戏角色的基本属性及常用数学方法。接着，深入探讨游戏智能体状态机的实现。通过简单足球游戏实例，本书给出用状态机实现游戏ai的例子。- Game artificial intelligence programming case essence mainly about how to make the role of the game with intelligent technology. This book fi
大数据下的机器学习算法综述
- 研究大数据环境下的机器学习算法成为学术界和产业界共同关注的话题. 文中主要分析和总结当前用于处理大数据的机器学习算法的研究现状.(Developing machine learning algorithms for big data is a research focus. In this paper, the state of the art machine learning techniques for big data are introduced and analyzed.)
Learning Deep Architectures for AI
- 一本关于深度架构学习算法，尤其是用来构造更深层模型的非监督学习的单层模型。(Theoretical results suggest that in order to learn the kind of com- plicated functions that can represent high-level abstractions (e.g., in vision, language, and other AI-level tasks), one may need deep archite
python machine learning
- 作者是Sebastian Raschka，密歇根州立大学的博士生，他在计算生物学领域提出了几种新的计算方法，还被科技博客Analytics Vidhya评为GitHub上最具影响力的数据科学家。他有一整年都使用Python进行编程的经验，同时还多次参加数据科学应用与机器学习领域的研讨会。在数据科学、机器学习以及Python等领域他拥有丰富的演讲和写作经验，本书可使得不具备机器学习背景的人设计出由数据驱动的解决方案。(The author, Sebastian Raschka, a PhD stu