LMS-MATLAB

Object programming on C++.

使用matlab编写的经纬高、东北天数据和地心坐标数据之间的转换函数文件，包含了东北天坐标系的定义说明文件以及相关的转换公式。 三个函数的调用文件名：ECEFtoENV，ECEFtoLBH，LBHtoECEF。使用说明见函数的说明。(Prepared using matlab high latitude and longitude, northeast-day data and geocentric coordinate conversion functions between data file that contains the definition of the coordinate system Northeast day documentation and related conversion formulas. Three function calls filename: ECEFtoENV, ECEFtoLBH, LBHtoECEF. See the instructions for use function.)

运用dds改进型算法 cordic算法实现将三角函数旋转任意角度的matlab代码(Using cordic to realize the manipulation of sin or cos function, which is changing their current phase into any given phase.)

对qpsk在高斯信道条件下合瑞利先到条件下的误码率进行了仿真(On the Gaussian channel in qpsk conditions together under the conditions of Rayleigh first simulated bit error rate)

renewable energy mode for beginers

主要用于计算目标前向、侧向、后向散射特征，同时完成RCS极坐标图的绘制(Used to calculate the target forward, sideways, backward scattering, and complete the drawing of the polar diagram RCS)

以比例导引律为基础，用伴随矩阵的构建解释了其闭环形式的解，其中包括初始航向角误差HED的图行，便于分析(The proportional guidance law as the foundation, with the adjoint matrix construction and explains its closed form solution, which includes the initial heading angle error of HED graphics, easy analysis)

说明：  使用Matlab编写的逆谐波程序。该程序对于不同的参数进行了实验。当图像噪声不同时，选用不同的参数。参数的正确选择很重要。本程序给出了不同噪声比较适合的参数选择(The use of Matlab procedures for the preparation of the inverse harmonic. The program parameters for different experiments. When the image noise is not at the same time, choosing different parameters. Correct choice of parameters is very important. This procedure gives more suitable for different noise parameters)

说明：  蚁群算法matlab实现，c为测试矩阵蚁群算法matlab实现，c为测试矩阵蚁群算法matlab实现，c为测试矩阵蚁群算法matlab实现，c为测试矩阵(matlab，ant matlab，ant matlab，ant matlab，ant matlab，ant matlab，ant )

The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access concepts. It is one of the most challenging issues in cognitive radio systems. In this paper, a survey of spectrum sensing methodologies for cognitive radio is presented. Various aspects of spectrum sensing problem are studied from a cognitive radio perspective and multi-dimensional spectrum sensing concept is introduced. Challenges associated with spectrum sensing are given and enabling spectrum sensing methods are reviewed. The paper explains the cooperative sensing concept and its various forms. External sensing algorithms and other alternative sensing methods are discussed. Furthermore, statistical modeling of network traffic and utilization of these models for prediction of primary user behavior is studied. Finally, sensing features of some current wireless standards are given.