Description: 基于C语言编写的利用BP算法训练人工神经网络的实际例子。-C language based on the use of BP algorithm for training artificial neural networks practical examples. Platform: |
Size: 41984 |
Author:王明 |
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Description: 用BP神经网络实现模糊控制规则为T=int[(e
+ec)/2]的模糊神经网络控制器。可以改变隐层节点数和学习速率。网络训练算法是变学习速率法。-BP neural network with fuzzy control rules for the T = int [(e+ Ec)/2] of the fuzzy neural network controller. Can change the hidden layer nodes and learning rate. Network training algorithm is a variable learning rate method. Platform: |
Size: 4096 |
Author:韩梅 |
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Description: 该程序包包含三个函数，一个用于建立BP神经网络，一个用于训练该网络，最后一个用于测试样本。-The package contains three functions, one for the establishment of BP neural networks, one for training the network, the last one for the test samples. Platform: |
Size: 3072 |
Author:culbert |
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Description: Gabor小波变换代码用于局部特征提取使用，又相当好的效果-Gabor texture descriptor have gained much attention for
different aspects of computer vision and pattern recognition.
Recently, on the rayleigh nature of Gabor filter outputs
Rayleigh model Gabor texture descriptor is proposed.
In this paper, we investigate the performance of these two
Gabor texture descriptor in texture classification. We built
a texture classification system based on BPNN, and use the
corresponding feature vector from traditional Gabor texture
descriptor or Rayleigh model one as input of BPNN. We use
three datasets from the Brodatz album database. For all
the three datasets, the original texture images are subdivided
into non-overlapping samples of size 32 × 32. 50
of the total samples are used for training and the rest are
used for testing. We compare the system training time and
recognition accuracy between two Gabor texture descriptor.
The experimental results show that, it takes more time when
using Rayleigh model Gabor texture descriptor than tr Platform: |
Size: 16384 |
Author:力量 |
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Description: 这个程序如何转化成训练BP神经网络连接权值的源代码,提供4组15输入4输出训练集和目标集,调整输出层加权系数.-How this program into training BP neural network connection weights of the source code, provides 4 inputs 4 outputs 15 training set and the target set, adjust the output layer weighting coefficients. Platform: |
Size: 1024 |
Author:zbs |
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Description: 程序用vc6.0编写，基于离散余弦变换DCT和bp神经网络的人脸识别。采用ORL人脸库，对图像进行DCT低通滤波，再用BPNN进行训练或识别，样本空间内识别效果好。设计流程参考了本站 yaxuan 的v3.3(http://www.pudn.com/downloads330/sourcecode/math/detail1452162.html)(本程序不包含原作的粒子群修正权值及网络结构调整等功能，但调整了训练样本的排列顺序) 感谢原作者，若有侵权我会删除此上传^ ^-Vc6.0 procedures used to prepare, transform and DCT bp neural network recognition based on discrete cosine. Use ORL face for image DCT lowpass filter, and then BPNN training or recognition, good recognition effect within the sample space. The design process of the reference site yaxuan v3.3 (http://www.pudn.com/downloads330/sourcecode/math/detail1452162.html) (The program does not contain particle swarm correction weights and network features such as the original restructuring but adjusted the order of training samples) thanks to the original, if tort I will remove this upload ^ ^ Platform: |
Size: 3476480 |
Author:连云 |
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Description: 前向型神经网络(BPNN)
1.首先使用随机函数对每一层间的连接权值矩阵和偏置向量进行随机初始化.
2.依次使用一个训练样本对网络进行训练，并按照上面的公式计算每个样本的Δti,t 1,...,T− 1
3.训练p个样本后(一次batch)，按照更新方程对W与b进行更新.
4.重复步骤2～3，直到误差小于设定的阈值或者达到设定的batch次数.-Forward neural network (BPNN) 1. First, using a random function of connection weight matrices and bias vectors between each layer of random initialization. 2 in order to use a training sample to train the network, and calculated according to the above formula Δti each sample, t 1, ..., T-1 3. training p samples after (a batch), according to the update equation of W and b are updated. 4. repeat steps 2-3 until the error is less than set threshold or reach the batch number of the set. Platform: |
Size: 4096 |
Author:王志坦 |
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Search - training of bpnn