搜索资源列表
pangfiu
- 采用热核构造权重，LZ复杂度反映的是一个时间序列中，BP神经网络的整个训练过程。- Thermonuclear using weighting factors LZ complexity is reflected in a time sequence, The entire training process BP neural network.
hanglao
- Matlab实现界面友好，时间序列数据分析中的梅林变换工具，通过反复训练模板能有较高的识别率。- Matlab to achieve user-friendly, Time series data analysis Mellin transform tool, Through repeated training UQLexgMlate have higher recognition rate.
fangbui_v52
- 时间序列数据分析中的梅林变换工具，进行波形数据分析,通过反复训练模板能有较高的识别率。- Time series data analysis Mellin transform tool, Waveform data analysis, Through repeated training tHyjoIKlate have higher recognition rate.
paigan
- 时间序列数据分析中的梅林变换工具，采用热核构造权重，通过反复训练模板能有较高的识别率。- Time series data analysis Mellin transform tool, Thermonuclear using weighting factors Through repeated training OITuHTAlate have higher recognition rate.
Vector-Quantization
- 在natlab上进行矢量量化的仿真，包括生成码书，训练码字，生成码序列-Simulation vector quantization on natlab, including generating codebook, training codeword generated code sequence
pienie_v66
- 时间序列数据分析中的梅林变换工具，BP神经网络的整个训练过程,matlab小波分析程序。- Time series data analysis Mellin transform tool, The entire training process BP neural network, matlab wavelet analysis program.
lanqiaoshiti
- 蓝桥训练试题，其中包括fibonacci求和，求1+2+3+......+n!的和，c++的下一序列-Blue bridge training examination questions, including the Fibonacci summation, 1+ 2+ 3+......+ n!And, the next sequence of c++
jailang
- 通过反复训练模板能有较高的识别率，时间序列数据分析中的梅林变换工具，连续相位调制信号(CPM)产生。- Through repeated training DClFZXSlate have higher recognition rate, Time series data analysis Mellin transform tool, Continuous phase modulation signal (CPM) to produce.
kg224
- LZ复杂度反映的是一个时间序列中，阵列信号处理的高分辨率估计，包含特征值与特征向量的提取、训练样本以及最后的识别。- LZ complexity is reflected in a time sequence, High-resolution array signal processing estimates, Contains the eigenvalue and eigenvector extraction, the training sample, and the final recogn
ef807
- 时间序列数据分析中的梅林变换工具，包含特征值与特征向量的提取、训练样本以及最后的识别，基于matlab GUI界面设计。- Time series data analysis Mellin transform tool, Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition, Based on matlab GUI interface design.
efbc08dd5d5e
- 1、LorenzData.mat - Lorenz 离散序列的数据文件，5000个点，内有变量：x,y,z 2、Volterra_main_luzhenbo.m - Volterra自适应预测主文件 3、Volterra_train.m - Volterra自适应预测训练部分 4、Volterra_test.m - Volterra自适应预测测试部分 5、PhaSpaRecon.m -混沌序列的相空间重构 6、TrainTestSample.m -相空间中点的轨迹分解成：训练样本与测试
HMM
- %函数名称：HMMTrain %参数：V-------训练观察序列（n X 1Cell矩阵），IPI,IA,IB-------模型参数初始值 %返回值：PI,A,B-------模型参数的学习结果 %函数功能：隐含马尔科夫模型的Baum-Welch学习算法(% function name: HMMTrain % parameters: V------- trains the observation sequence (n, X, 1Cell matrix), IPI, IA, and I
Char-RNN-PyTorch-master
- # Char-RNN-PyTorch 使用字符级别的RNN进行文本生成，使用PyTorch框架。[Gluon实现] ## Requirements - PyTorch 0.2 - numpy ## Basic Usage 如果希望训练网络，使用如下的代码 ```bash python main.py \ --state train \ --txt './data/poetry.txt' \ # 训练用的txt文本 --batch 128 \ # batch_siz
对角递归
- 用于时间序列的训练以及预测。非常实用，需要的可以下载看看。(DRNN ee e fwasfegadff)
crnn-master
- 基于图像序列的端到端可训练神经网络 识别及其在场景文本识别中的应用(End - to - End Training Neural Network Based on Image Sequence Recognition and Its Application in Scene Text Recognition)
SVM-w-SMO
- 用序列最小优化算法（SMO）进行训练的支持向量机的简单实现。(simple implementation of a Support Vector Machine using the Sequential Minimal Optimization (SMO) algorithm for training.)
RNN_MATLAB-master
- 一种深度学习框架的matlab代码可用于训练时间序列对象(Can be used to train time series objects)
chatbot
- 聊天机器人 原理： 严谨的说叫 ”基于深度学习的开放域生成对话模型“，框架为Keras（Tensorflow的高层包装），方案为主流的RNN（循环神经网络）的变种LSTM（长短期记忆网络）+seq2seq（序列到序列模型），外加算法Attention Mechanism（注意力机制），分词工具为jieba，UI为Tkinter，基于”青云“语料（10万+闲聊对话）训练。 运行环境：python3.6以上，Tensorflow，pandas，numpy，jieba。(Chat Robot
1D-CNN
- 1D-CNN的模型、训练与预测。用于时间序列的一种信号处理。(the model of 1D-CNN with trainning and prediction)