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基于BP网络的印刷体数字识别
- 基于BP网络的印刷体数字识别技术的完整案例，对图像处理及其BP神经网络付有完整的程序，并可以允许，同时还附有大量的测试图片-Digit recognition technology integrity cases, right image processing and neural network BP to pay the full process and allows, but also with a large number of test pictures
ATRalgorithms
- 一种图像自动识别算法，该方法：通过提取图像7个不变矩，结合神经网络(BP)对图像目标进行识别计算．结果表明， 该算法具有很好的识别效果，可以应用于图像小目标的识别．-an automatic image recognition algorithm, the method : extract images through seven unchanged moments, integrated Neural Network (ANN) to the identification of targe
0~9bp_train
- 用matlab实现数字识别,方法为bp神经网络,该程序实现了对数字识别的训练过程.-using Matlab digital identification methods bp neural network, The realization of the digital identification of the training process.
BPNet
- 几种C++神经模型和算法实例,主要有BP神经网络、BP神经网络解决异或问题、HMM的C语言实现、矢量量化的C语言实现等。-Several C++ examples of neural models and algorithms, there are BP neural network, BP neural network to solve XOR problem, HMM of the C language, vector quantization, such as the C language
VCPbpPimprovePworking
- 用VC++实现的，超级好用的神经网络源代码，BP算法,超好用,超简洁 ，，已经测试过可直接运行-With VC++ achieve, super easy to use neural network source code, BP algorithm, super useful, super simple, have been tested can be run directly
Neural-Network--License-Recognition
- VC++的BP神经网络车牌识别，使用BP神经网络能较好的实现车牌的定位与识别-Vc++ the license plate recognition, BP neural network using the BP neural network can better realize the license plate location and recognition
BPANN
- 基于BP神经网络的字符识别算法源代码，包括网络仅值训练方法，训练是通 过调用34个字符文件夹，识别率达到99.8 。-BP neural network-based character recognition algorithm source code, including the value of the network only training methods, training is by calling the 34-character file folders, the r
OneBpNeural
- 一阶控制系统与BP神经网络PID控制功能是高斯白噪声干扰的Matlab程序-One-order control system with BP neural network PID control function is Gaussian white noise interference Matlab program
BP-and-SOM
- BP（Back Propagation）网络是一种按误差逆传播算法训练的多层前馈网络，是目前应用最广泛的神经网络模型之一。 BP网络能学习和存贮大量的输入-输出模式映射关系，而无需事前揭示描述这种映射关系的数学方程。 它的学习规则是使用最速下降法，通过反向传播来不断调整网络的权值和阈值，使网络的误差平方和最小。BP神经网络模型拓扑结构包括输入层（input）、隐层(hide layer)和输出层(output layer)。 通过对信息的提取以及