This methodical text aspires to present various information relevant to operating systems, computer architecture, compilers, principles of programming languages, and C and C++ programming, specifically.
The release of the Microsoft Visual Studio .NET (and Visual C++ .NET in particular) has underscored Microsoft’s increasing focus on Internet technologies, which are at the heart of the Microsoft .NET architecture. In addition to supporting the .NET initiative, Visual C++ .
The TMS320C54x, TMS320LC54x, and TMS320VC54x fixed-point, digital signal processor (DSP) families
(hereafter referred to as the ’54x unless otherwise specified) are based on an advanced modified Harvard
architecture that has one program memory bus and three data memory buses. These processors also ...
FatFs06.rar
FatFs is a generic file system module to implement the FAT file system to small embedded systems. The FatFs is written in compliance with ANSI C, therefore it is independent of hardware architecture. It can be incorporated into cheap microcontrollers, such as 8051, PIC, AVR, SH, Z80, H8, ...
The System Management BIOS Reference Specification addresses how motherboard and system vendors present
management information about their products in a standard format by extending the BIOS interface on Intel
architecture systems. The information is intended to allow generic instrumentation to deli ...
DDR SDRAM控制器的VHDL源代码，含详细设计文档。
The DDR, DCM, and SelectI/O™ features in the Virtex™ -II architecture make it the perfect
choice for implementing a controller of a Double Data Rate (DDR) SDRAM. The Digital Clock
Manager (DCM) provides the required Delay Locked Loop (DLL), Dig ...
Batch version of the back-propagation algorithm.
％ Given a set of corresponding input-output pairs and an initial network
％ [W1,W2,critvec,iter]=batbp(NetDef,W1,W2,PHI,Y,trparms) trains the
％ network with backpropagation.
％
％ The activation functions must be either linear or tanh. The network
...
％ Train a two layer neural network with the Levenberg-Marquardt
％ method.
％
％ If desired, it is possible to use regularization by
％ weight decay. Also pruned (ie. not fully connected) networks can
％ be trained.
％
％ Given a set of corresponding input-output pairs and an initial
％ network,
％ ...
