OpcClient

64QAM解调文章，在符号同步方面，采用插 值滤波器的设计，在盲均衡方面，提出了改进算法--MMA+HCMA双模式算法，利用MMA算法对信号的实部和虚部都进行均衡的原理解决了CMA+HCMA算法盲相位的问题(64QAM demodulation article, the symbol synchronization, using the interpolation filter design, blind equalization, the proposed improved algorithm- MMA+ HCMA dual-mode algorithm, the use of MMA algorithm to signal the real and imaginary parts of the balanced CMA+ HCMA principle to solve the problem of algorithm-blind phase)

Visual C++高级开发范例解析第二章ActiveX源码(Visual C++ Advanced Development ActiveX sample chapter source analysis)

说明：  面阵中的DOA估计，利用ESPRIT进行估计(DOA estimation in plane array is performed by ESPRIT)

说明：  一种轻便高效的数据格式，平台无关、语言无关、可扩展，可用于通讯协议和数据存储等领域。完整的编译工程。(A portable and efficient data format, platform-independent, language-independent, scalable, can be used in communication protocols and data storage and other fields. Complete compilation engineering.)

基本波束成形相关算法实现。方向图函数的代码实现。最优权准则的实现(The basic beamforming algorithm is implemented. The code implementation of the pattern function. The realization of the optimal weight criterion)

利用matlab自适应滤波器实现心电信号的去噪 自适应滤波器 心电图(De-Noising of Electrocardiogram (ECG) with Adaptive Filter Using MATLAB)

OFDM 自适应算法能够根据信道的状况进行比特和功率的分配，能够有效的降低误码率.本程序综合了迭代注水算法，CHOW算法，FISHER算法，H-H算法，以及自己改进的迭代注水算法程序，并进行了对比，改进的算法在有效性与迭代注水算法基本相近，但复杂度和实际应用性都更强，值得参考。(OFDM adaptive algorithm make the bit and power allocation according to the status of the channel .It can effectively reduce the error rate.This program combines iterative algorithm, water injection CHOW algorithm, FISHER algorithm, the algorithm of H- H,as well as their improved iterative allocation algorithm procedures.And has carried on the contrast, the improved algorithm in effectiveness and iterative allocation algorithm basic similar, but the complexity and practical applications were stronger with worthy of reference.)

working of the fifth generation intelligent radio that is Cognitive Radio (CR) system which works on predictive data rate and propose ANFIS based learning scheme to introduce intelligence in it. The testing data set is taken from training set. Validation data set is unseen data. RMSE and prediction accuracy are used as performance index. Two gaussian membership functions are taken for each input. Error goal was set for .001.Training was for 300 epochs. It is seen prediction accuracy was 91 percentages in testing case and 89 in validation. RMSE difference between validation and testing case very small.

默认产生（0，1）的高斯随机数，参数可调(Gauss random number (0,1) is generated by default with adjustable parameters.)

HLP A+ Modbus 标准通讯协议格式，上位机发送数据格式，正确时变频器返回数据格式(This bit will be set to logic 1 when the receive buffer has been read and contains no new information. If there is new information available in the receive buffer that has not been read, this bit will return to logic 0. RXBMT = 1 when in Master Mode.)