Description: 基于keras的python的循环神经网络rnn,对数据库minis进行的分类。希望大家喜欢-Based keras the python loop neural network rnn, minis conduct classification. I hope you like Platform: |
Size: 1024 |
Author:yaxon |
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Description: 基于keras的python的转换的卷积神经网络,对数据库minis进行的分类。希望大家喜欢-Based on Convolution neural network keras of python conversion, minis conduct classification. I hope you like Platform: |
Size: 2048 |
Author:yaxon |
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Description: 可以实现模式识别领域的数据的分类及回归,是机器学习的例程,是一种双隐层反向传播神经网络。- You can achieve data classification and regression pattern recognition, Machine learning routines, Is a two hidden layer back propagation neural network. Platform: |
Size: 7168 |
Author:高晓建 |
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Description: 自己编的5种调制信号,是一种双隐层反向传播神经网络,Relief计算分类权重。- Own five modulation signal, Is a two hidden layer back propagation neural network, Relief computing classification weight. Platform: |
Size: 4096 |
Author:薛启宏 |
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Description: 基于人工神经网络的常用数字信号调制,Relief计算分类权重,计算时间和二维直方图。- The commonly used digital signal modulation based on artificial neural network, Relief computing classification weight, Computing time and two-dimensional histogram. Platform: |
Size: 5120 |
Author:李小松 |
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Description: RNN神经网络的基本概念。改进的RNN神经网络的基本概念的应用-Sequence prediction and classification are ubiquitous and challenging problems in machine learning that can require identifying complex dependencies between temporally distant inputs. Recurrent Neural Networks (RNNs) have the ability,
in theory, to cope with these temporal dependencies by virtue of the short-term memory implemented by their recurrent (feedback) connections.
However, in practice they are difficult to train successfully when the long-term memory is required.
This paper introduces a simple, yet powerful modification to the standard RNN architecture, the
Clockwork RNN (CW-RNN), in which the hidden
layer is partitioned into separate modules, each
processing inputs at its own temporal granularity,
making computations only at its prescribed clock
rate. Rather than making the standard RNN models more complex, CW-RNN reduces the number
of RNN parameters, improves the performance
significantly in the tasks tested, and speeds up the
network uation. The network is demo Platform: |
Size: 606208 |
Author:大夫 |
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Description: BP神经网络 ,用于数据预测和曲线拟合等二分类问题-BP neural network for data prediction and curve fitting and other two classification problems Platform: |
Size: 2048 |
Author:make |
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Description: 包含特征值与特征向量的提取、训练样本以及最后的识别,关于神经网络控制,可以实现模式识别领域的数据的分类及回归。- Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition, On neural network control, You can achieve data classification and regression pattern recognition. Platform: |
Size: 7168 |
Author:qui |
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Description: 基于BP网络的语言识别,选取民歌、古筝、摇滚和流行四类不同音乐,用BP神经网络实现对这四类音乐的有效分类。-Speech recognition based on BP network, songs, zither, four different types of rock and pop music, with BP neural network classification of these four types of music valid. Platform: |
Size: 373760 |
Author:zhanglei |
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Description: SVM神经网络的数据分类预测-葡萄酒种类识别,能够很好地预测葡萄酒种类。-SVM neural network data classification prediction- wine species identification, can be a good predictor of wine types. Platform: |
Size: 39936 |
Author:乐乐 |
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Description: 基于bp神经网络进行大量数据的分类分析训练。-Large amounts of data based on bp neural network classification analysis training. Platform: |
Size: 4096 |
Author:tom |
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