drtoolbox-use

说明：  基于双耦合Duffing振子的随机相位正弦信号检测 采用双耦合混沌振子阵列实现了随机相位微弱正弦信号的检测，在此基础上，提出了新的检测方法，即利用单个耦合混沌振子，通过临界及周期状态 的变化检测随机相位微弱正弦信号并大致估计信号相位范围，该方法比双耦合混沌振子阵列法简单，更易于实现。(Based on double coupled Duffing oscillators random phase sine signals detected by two coupled chaotic oscillator arrays to achieve a random phase weak sinusoidal signal detection, in this basis, the proposed new detection methods, namely the use of a single coupled chaotic oscillators, through the critical and the cycle random phase state change detection and generally weak sinusoid signal phase estimated the scope of the method than the two-coupled chaotic oscillators array method is simple and more easy to implement.)

ADVANTAGE: The main advantage of the NLMS algorithm over the LMS algorithm is the faster convergence for correlated[11] and whitened input and the stableness of the output with the varying range of values independent input data[12]. And to implement a shift input of data the NLMS require additional addition, Multiplication and division over the LMS algorithm.

这是一个的10Mb文件 这是演示版本的SIGTOOL软件包。 它没有完整的文件导入功能或速度的完整版本sigTOOL (this is a 10Mb file THIS IS A DEMO VERSION OF THE SIGTOOL SOFTWARE PACKAGE. It does not have the complete range of file import functions or speed of the full version of sigTOOL. )

upml边界条件下的FDTD程序，感觉很不错，分享给大家吧，也希望大家能更多的分享自己的程序。谢谢(boundary conditions under upml FDTD program, I feel very good, for everyone to share it, I hope you will be able to share their program more. Thank you)

说明：  基于Harris的掌纹图像特征提取的程序，非常的完整可靠(Harris based on palmprint image feature extraction procedures, very full and reliable)

最近从书上看到的非线性解题法的一个程序，共享下(Recently from the book to see non-linear problem-solving method of a program to share the)

i am in need 4g related matlab code.i learning in area of lte-advanced downlink for writing the matlab code

Related to Digital Image Processing

说明：  遗传算法，简单易懂。适合初学者使用，是分布式电源的选址定容的算法，做了相应的改进(Classical genetic algorithm is simple and easy to understand. It is suitable for beginners to use. It is an algorithm for locating and sizing distributed power.)

经过调试的很好用的svm分类程序，真的很好用(After commissioning of the good use of the svm classification procedures, is actually pretty good)