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Hermit多项式在线学习ran算法
- 本程序用资源分配网(Resource_Allocation Network,简称RAN)实现了Hermit多项式在线学习问题。训练样本产生方式如下,样本数400,每个样本输入Xi在区间[-4,4]内随机产生(均匀分布),相关样本输出为F(Xi) = 1.1(1-Xi + Xi2)exp(-Xi2/2),测试样本输入在[-4,+4]内以0.04为间隔等距产生,共201个样本。训练结束后的隐节点为:11个,训练结束后的平均误差可达:0.03 -this program resources dis
bpxl
- 通过bp算法的代码介绍运用bp算法进行训练学习的作用,已经可以在matlab7中运行。-bp algorithm through the use of code introduced bp algorithm for training to learn, matlab7 can already run.
Fuzzycontrol
- 模糊神经控制基于网络bp的源代码用于训练学习
2007010238
- 基于决策树和贝叶斯的预测分析器,可以对数据库中的数据集通过训练学习后根据训练结果进行信息预测。
简单手写体数字识别系统的源代码
- 为了实现对手写字体的识别,运用了人工智能的分层神经网络思想,对识别的字体通过训练学习,达到识别手写字体的功能。-order to achieve the recognition of handwritten characters, the use of artificial intelligence hierarchical neural network thinking, the right font identification through training to learn, to a
SR_1
- 基于分块的人脸图像超分辨率学习算法实验平台,利用学习到的训练集图像信息对低分辨率图像超分辨率,并可以查看超分辨率后的图像块匹配结果(用鼠标双击结果显示窗口中的实验图像),可以设置实验参数。-Block-based face image super-resolution algorithm for the experimental platform to learn, learning to use the training set of low-resolution image informat
svmclass
- 采用经典的机器学习分类算法SVM,对训练样本进行训练和学习,来实现对预定目标的分类。-Using the classic machine learning classification algorithm SVM, the training samples for training and study to achieve the intended target of the classification.
yuce
- 一个BP网络的MATLAB源代码,通过训练学习,进而对目标的预测-A BP network of MATLAB source code to learn through training and then on the target forecast
TextClustering
- 文本聚类,VC编程实现,作为一种无监督的机器学习方法,聚类由于不需要训练过程,以及不需要预先对文档手工标注类别,因此具有一定的灵活性和较高的自动化处理能力-Text Clustering, VC programming, as an unsupervised machine learning method, clustering by eliminating the need for the training process, and do not need to manually pre-ma
OS-ELM在线极限学习机
- 此代码是OS-ELM在线极限学习机,内含训练集和测试集。(This code is the OS-ELM online extreme learning machine, containing training set and test set.)
Deep_Learning(深度学习)
- 深度学习入门教程,由浅入深,包含深度学习的基本思想,各种训练模型已经卷积神经网络相关内容(Deep learning introduction course, from shallow to deep, including deep learning basic ideas, various training models have convolution neural network related content)
极限学习机
- 极限学习机分类器,训练函数与预测函数,以及数据实例(Extreme Machine Classifiers, Training and Prediction Functions, and Data Instances)
机器学习实战
- 讲解机器学习,用个大案例进行学习分心,包括代码编写,训练,模型建立,模型使用方法(Explain machine learning, use a large case for learning distractions, including code writing, training, model building, and model use)
多任务深度学习改进版
- 这个程序实现了多任务的深度学习,可以提高训练的收敛速度(Multi-task deep learning)
基于极限学习机的预测
- 针对非线性预测问题,建立极限学习机的预测模型,将数据样本分为训练样本和测试样本,并采用误差指标进行评价。(Aiming at the problem of non-linear prediction, the prediction model of extreme learning machine is established. The data samples are divided into training samples and test samples, and the error i
基于极限学习机ELM的数据分类
- 针对数据分类问题,提出了基于极限学习机的分类方法,将数据样本分为训练样本和测试样本,并采用准确率指标进行评价。(Aiming at the problem of data classification, a classification method based on extreme learning machine is proposed. The data samples are divided into training samples and test samples, and the
基于深度强化学习的复杂环境下机器人自主移动算法
- 本算法是通过深度强化学习方法,模拟人类行走策略,建立避免碰撞的模型,训练机器人底盘以人类习惯在复杂变化的环境中主动生成速度和角度信息,从而自动行走。
KNN学习
- KNN学习,通过测试集和训练集进行预测KNN学习,(KNN learns to predict through test set and training set)
基于深度学习的二进制代码漏洞检测系统
- 二进制代码漏洞检测是一个重要的研究问题。针对当前基于静态分析的二进制代码漏洞检测系统普遍存在误报率高,检测粒度粗,且依赖专家经验等问题,提出了用库/API函数调用程序切片细粒度表示二进制程序,并引入深度学习技术,自动检测二进制程序中库/API函数调用相关漏洞,设计并实现了一个基于深度学习的二进制代码漏洞检测系统——BVDetector。该系统通过对二进制程序进行控制流和数据流分析,从程序中提取库/API函数调用的程序切片,并为程序切片添加有无漏洞的标签;然后将程序切片转换成符合漏洞检测深度学习模
基于特殊训练序列的蒙特卡洛信道估计与误码率仿真
- 基于特殊训练序列的蒙特卡洛信道估计与误码率仿真(含h_decimation.am文件) 本文档仅供学习交流之用,禁止用于商业用途!违者责任自负!!!(Monte carlo channel estimation and bit error rate simulation based on special training sequence (including h_decimation. Am file) This document is for learning and communicati