代码搜索:NETWORKS

找到约 10,000 项符合「NETWORKS」的源代码

代码结果 10,000
www.eeworm.com/read/103743/15724424

c win32.c

/* * OpenVPN -- An application to securely tunnel IP networks * over a single UDP port, with support for SSL/TLS-based * session authentication and key exchange, *
www.eeworm.com/read/103743/15724445

h reliable.h

/* * OpenVPN -- An application to securely tunnel IP networks * over a single UDP port, with support for SSL/TLS-based * session authentication and key exchange, *
www.eeworm.com/read/103743/15724454

c session_id.c

/* * OpenVPN -- An application to securely tunnel IP networks * over a single UDP port, with support for SSL/TLS-based * session authentication and key exchange, *
www.eeworm.com/read/103743/15724461

h win32.h

/* * OpenVPN -- An application to securely tunnel IP networks * over a single UDP port, with support for SSL/TLS-based * session authentication and key exchange, *
www.eeworm.com/read/103743/15724489

c fdmisc.c

/* * OpenVPN -- An application to securely tunnel IP networks * over a single UDP port, with support for SSL/TLS-based * session authentication and key exchange, *
www.eeworm.com/read/103743/15724495

h integer.h

/* * OpenVPN -- An application to securely tunnel IP networks * over a single UDP port, with support for SSL/TLS-based * session authentication and key exchange, *
www.eeworm.com/read/103743/15724498

in config-win32.h.in

/* * OpenVPN -- An application to securely tunnel IP networks * over a single UDP port, with support for SSL/TLS-based * session authentication and key exchange, *
www.eeworm.com/read/290419/8484068

c tun.c

/* * OpenVPN -- An application to securely tunnel IP networks * over a single TCP/UDP port, with support for SSL/TLS-based * session authentication and key exchange, *
www.eeworm.com/read/290419/8484072

h tun.h

/* * OpenVPN -- An application to securely tunnel IP networks * over a single TCP/UDP port, with support for SSL/TLS-based * session authentication and key exchange, *
www.eeworm.com/read/287267/8699032

m mregwav1.m

% Example of multiscale approximation using % Regularization Networks % % Learning parameters "lambda" have to be tuned % for instance by means of a cross-validation. % Wavelet frame are used f