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C语言写的神经网络源程序
- C语言写的神经网络源程序,小弟从网上下载了,看不懂,提供给大家共同研究-write C-language source of neural network, the younger brother downloaded from the Internet, to understand, to the common study
AIcode
- 人工智能人工神经网络源码 c语言代码 来源:源码中国-AI Artificial Neural Network c language source code Source : China FOSS
BPinC
- 基于c语言的神经网络程序 不错的呀,夸夸下-based on the neural network programming good ah, herself under
CTHREAD
- 神经网络模拟系统和多任务应用系统开发的C语言源程序-neural network simulation system and multi-task operating system at the C language source
waveletann_c_code_notcopy
- 小波人工神经网络C语言实现(代码),以及相关支持库,已调试,可运行.
bp
- 神经网络中的BP算法,用C语言写的源代码,仅供大家参考。共同学习
BPC
- C语言编写的BP神经网络算法,通用性比较强,读着只需要在使用时改掉几个传递参数即可调用
NCC
- 神经网络7种C语言实现代码,大家可以
example1
- 人工神经网络, Ann C语言实现,经验正
BPalgorithm
- bp神经网络算法,是用c语言实现的,比较简单,供初学者练手-bp neural network algorithm
bpnn_batch
- 利用C++语言编写的BP批处理神经网络程序-The use of C++ language to prepare a batch of BP neural network program
shenjingwangluo
- 神经网络开发包用C++语言来编写的一段程序,不足之处请多指教。-Neural network development kit with C++ language section of the preparation of procedures, the inadequacy of advice please.
bpxor
- 用c语言实现了bp神经网络解决异或问题的算法,已经调试通过了-implement the bp xor through c
BP
- BP神经网络C语言程序 进行BP训练 可根据需要更改数据进行BP训练测试-BP neural network C language program for BP training may need to change the data according to BP training tests
BP
- BP神经网络C语言算法,对了解神经网络原理非常有帮助。-BP neural network algorithm in C language, and very helpful to understand the neural network theory.
neuralnetworks
- BP神经网络C语言实现,2个隐含层,隐含层节点可以调整,学习判断棋局胜负,数据已在压缩包中。-BP neural network C language, two hidden layer, hidden layer nodes can adjust and learn to judge the outcome of the chess game, the data is already compressed package.
C-realization-neural-network
- 人工神经网络的c语言实现,用于模式识别、最优化问题求解等-C language realizing artificial neural networks for pattern recognition, optimization problem solving, etc.
bp_rbf
- rbf神经网络 c语言代码 包含整个C语言工程及示例-rbf neural networks
机器学习
- c++语言实现的bp神经网络 机器学习 输入3个数据输出第四个数据 误差根据学习迭代次数的增加而下降(C++ language BP neural network machine learning input, 3 data output, fourth data errors according to the number of learning iterations increase decline)