Search - network in delphi

Search - network in delphi - List

[AI-NN-PR] fann-2.1.0beta DL : 0: Fast Artificial Neural Network Library是一个免费开源的神经网络库，它用C实现了支持全连接及稀连接的多层人工神经网络，并且支持定点和浮点数的跨平台运行。库中包含有易于处理训练数据的框架。它易于使用、通用、文档完备并且快速。目前已有PHP, C++, .NET, Ada, Python, Delphi, Octave, Ruby, Prolog Pure Data 和 Mathematica的绑定。库中还附有一本带例子和关于如何使用本库的建议的参考手册，本库也有一个可用的图形用户接口。-Fast Artificial Neural Network Library is a free open source neural network library, it uses C to achieve full connectivity and dilute support for multi-layer artificial neural network connections, and supports fixed and floating-point cross-platform operation. Library contains easy to handle training data framework. It is easy to use, universal, comprehensive documentation and quick. At present, PHP, C++,. NET, Ada, Python, Delphi, Octave, Ruby, Prolog Pure Data and Mathematica bindings. The library is accompanied with an example of how to use the library and on the recommendations of the reference manual, available in this library also has a graphical user interface.
Date : 2025-12-27 Size : 3.85mb User : hopper
[AI-NN-PR] NormalBPNet DL : 0: 用Delphi实现的标准BP神经网络算法，测试数据以txt文件给出，在文件夹下有。-Delphi to achieve with the standard BP neural network algorithm, the test data to txt file are given in the folder under.
Date : 2025-12-27 Size : 452kb User : 高雅田
[AI-NN-PR] Delphi_RBF_MRAC_Direct DL : 0: 这是用Delphi编写的关于RBF神经网络的MRAC直接算法的程序，希望对大家有所帮助，我也很愿意与大家分享这些代码。-It is written in Delphi RBF neural network on direct MRAC algorithm program, we want to help, I am very willing to share the code.
Date : 2025-12-27 Size : 239kb User : lixiangyang
[AI-NN-PR] FANN-2.2.0-Source DL : 0: FANN 2.20 Source code.Fast Artificial Neural Network Library是一个免费开源的神经网络库，它用C实现了支持全连接及稀连接的多层人工神经网络，并且支持定点和浮点数的跨平台运行。库中包含有易于处理训练数据的框架。它易于使用、通用、文档完备并且快速。目前已有PHP, C++, .NET, Ada, Python, Delphi, Octave, Ruby, Prolog Pure Data 和 Mathematica的绑定。库中还附有一本带例子和关于如何使用本库的建议的参考手册，本库也有一个可用的图形用户接口-FANN 2.20 Source code.Fast Artificial Neural Network Library is a free open source neural network library, it uses C to achieve full connectivity and dilute support for multi-layer artificial neural network connections, and supports fixed and floating-point cross-platform operation. Library contains easy to handle training data framework. It is easy to use, universal, comprehensive documentation and quick. At present, PHP, C++,. NET, Ada, Python, Delphi, Octave, Ruby, Prolog Pure Data and Mathematica bindings. The library is accompanied with an example of how to use the library and on the recommendations of the reference manual, available in this library also has a graphical user interface.
Date : 2025-12-27 Size : 2.24mb User : 兰虹丞