MATLABCSharp

非线性量化。读取wav文件，用2到12比特数量化。抽样频率8KHz。()

产生2ASK、4ASK、8ASK的m文件和产生的mat格式的数据文件。(Generated 2ASK, 4ASK, 8ASK of m documents and produced mat format data files.)

该模型实现了一个通用的OFDM TX和RX，这是不依赖于任何特定的行业标准。该模型的目标是开发和研究不断（不是“突发”）载波同步和定时跟踪方案。该技术纳入然后可以扩展和修改，以标准的具体通讯套件。该模型采用了“收购”技术，它利用了循环前缀相关属性，以赶在试图完成罚款跟踪算法一帧的边界粗略的估计。该模型实现了一个16点64循环前缀的OFDM载波波形。在OFDM符号有16个飞行员，3后卫音（0，带边幅），并使用45 QAM的剩余数据流4。 这包括最新型的衰落信道，误码率计算，并改善控制回路动态。(This model implements a generic OFDM TX and RX, which is not tied to any particular industry standard. The objective of this model is to develop and explore a continuous (not “bursty”) carrier and timing tracking synchronization scheme. The techniques incorporated can then be extended and modified to suite specific communications standards. The model uses an “acquisition” technique that exploits the correlation properties of the cyclic prefix to get a rough estimate of the frame boundary before attempting to accomplish the fine tracking algorithms. The model implements a 64 carrier OFDM waveform with a 16 point cyclic prefix. The OFDM symbol has 16 pilots, 3 guard tones (0 amplitude at band edge) and uses 4 QAM for the 45 remaining data streams. This latest model includes a fading channel, BER computation, and improved control loop dynamics. )

this is a well data number 1 for RPH sample, stored in las format

一个利用matlab来模拟数字信号处理过程的，信号经过加噪声滤波后重新输出。(a simulation using Matlab to digital signal processing, signal plus noise filtering through re-export.)

自相关法谱估计的程序，这是一种经典的方法，效果真心不错(Autocorrelation spectrum estimation procedure, which is a classic method, the effect is really good)

SUBTRACTIVE CLUSTERING ALGORITHM

Hiding of data in the images

S-Function（系统函数）为扩展Simulink® 的性能提供了一个有力的工具。以下下节阐述了什么是 S-Function，为什么可以使用S-Function，以及怎样编写自己的S-Function。(S-Function (system function) for the expansion of the performance of Simulink ® provides a powerful tool. The following section describes what is under the S-Function, Why you can use the S-Function, and how to write your own S-Function.)

the k-modes algorithms for clustering algorithms.......