This tutorial attempts to get you started developing with the Win32 API as quickly and clearly as possible. It is meant to be read as a whole, so please read it from beginning to end before asking questions... most of them will probably be answered. Each section builds on the sections before it. I have also added some solutions to common errors in Appendix A. If you ask me a question that is answered on this page, you will look very silly.
This manual describes omniidl, the omniORB IDL compiler. It is intended for developers
who wish to write their own IDL compiler back-ends, or to modify existing
ones. It also documents the design of the compiler front-end for those poor souls
who have to track the IDL specification.
The goal of this library is to make ODBC recordsets look just like an STL container. As a user, you can move through our containers using standard STL iterators and if you insert(), erase() or replace() records in our containers changes can be automatically committed to the database for you. The library s compliance with the STL iterator and container standards means you can plug our abstractions into a wide variety of STL algorithms for data storage, searching and manipulation. In addition, the C++ reflection mechanism used by our library to bind to database tables allows us to add generic indexing and lookup properties to our containers with no special code required from the end-user. Because our code takes full advantage of the template mechanism, it adds minimal overhead compared with using raw ODBC calls to access a database.
This simple program help you to calculate parameters for a pid controller for first order systems wiith delay using different method: Ziegler Nichols,Cohen coon,IMC...
This leon3 design is tailored to the Altera NiosII Startix2
Development board, with 16-bit DDR SDRAM and 2 Mbyte of SSRAM.
As of this time, the DDR interface only works up to 120 MHz.
At 130, DDR data can be read but not written.
NOTE: the test bench cannot be simulated with DDR enabled
because the Altera pads do not have the correct delay models.
* How to program the flash prom with a FPGA programming file
1. Create a hex file of the programming file with Quartus.
2. Convert it to srecord and adjust the load address:
objcopy --adjust-vma=0x800000 output_file.hexout -O srec fpga.srec
3. Program the flash memory using grmon:
flash erase 0x800000 0xb00000
flash load fpga.srec
Using the UnderC Tokenizer Class
It s often necessary to parse complex text files, where standard i/o
is too clumsy. C programmers fall back on strtok(), but this can be
tricky to use properly. Besides, you are still responsible for keeping
strtok() fed with new input, and I don t like the schlepp.
Tokenizer is a text-parsing input stream, modelled after the (undocumented)
VCL TParser class, and based on the UnderC tokenizing preprocessor front-end.
Welcome to UnderC version 1.2.9w
This package consists of the executable (UCW), a default script file,
this file, and the library files. It is important that the header files
end up in a include subdirectory of the directory where UCW is found.
If you unzip this file using its path information ( use folder names ) this will
automatically happen. You can optionally specify the UnderC directory
with the environment variable UC_HOME note that this points to the directory
containing ucw.exe. If you do this, then you can copy the executable anywhere
and it will still be able to find the header files.
This example streams input from a ADC source to a DAC.
An analog signal is acquired block-by-block into SDRAM from the ADC (an AD9244 in this example).
The frames are then output with a one-frame delay to the DAC (an AD9744 in this example).
In this example, no processing is done on the frames. They are passed unaltered.
Boosting is a meta-learning approach that aims at combining an ensemble of weak classifiers to form a strong classifier. Adaptive Boosting (Adaboost) implements this idea as a greedy search for a linear combination of classifiers by overweighting the examples that are misclassified by each classifier. icsiboost implements Adaboost over stumps (one-level decision trees) on discrete and continuous attributes (words and real values). See http://en.wikipedia.org/wiki/AdaBoost and the papers by Y. Freund and R. Schapire for more details [1]. This approach is one of most efficient and simple to combine continuous and nominal values. Our implementation is aimed at allowing training from millions of examples by hundreds of features in a reasonable time/memory.
The line echo canceller (LEC) is designed to provide the maximum attainable transparent voice quality for
de-echoing of a PSTN or POTS connection in voice-over-LAN systems with internal delays, or on a codec end of a telecom switch,基于TI 54X/55X平臺
