FDTD_TE_TM_6

pid controller design matlab simulink blocks

人工神经网络用Sanger算法求解多个模式的主分量问题。(Sanger method using artificial neural network model for solving the main component of many problems.)

文章有utd对爬行波进行循迹 给出微分几何算法 可在matlab 及vc来开发(Utd article has crawling wave of differential geometry tracking algorithm is given in the matlab and vc to develop)

stardard scm channel model(standard scm channel model)

异步电机矢量控制仿真 波形很好 真的(Simulation waveform vector control induction motor is really good)

matlab绘制16QAM误码率曲线及星座图(MATLAB 16QAM BER)

使用matlab实现系统仿真的研究，电子书(Use of system simulation matlab implementation, e-books)

Matlab code for prediction exon regions in DNA strand

基于LMS算法的自适应均衡器!!!!!!!!!!!!!!!!!!(LMS-based adaptive equalizer algorithm)

迭代自适应Simpson，Lobatto积分 In almost every standard book on numerics quadrature algorithms like the adaptive Simpson or the adaptive Lobatto algorithm are presented in a recursive way. The benefit of the recursive programming is the compact and clear representation. However, recursive quadrature algorithms might be transformed into iterative quadrature algorithms without major modifications in the structure of the algorithm. We present iterative adaptive quadrature algorithm (adaptiveSimpson and adaptiveLobatto), which preserves the compactness and the clarity of the recursive algorithms (e.g. quad, quadv, and quadl). Our iterative algorithm provides a parallel calculation of the integration function, which leads to tremendous gain in run-time, in general. Our results suggest a general iterative and not a recursive implementation of adaptive quadrature formulas, once the programming language permits parallel access to the integration function. For details the attached PDF file Conrad_08.pdf. (Iterative Adaptive Simpson, Lobatto Points In almost every standard book on numerics quadrature algorithms like the adaptive Simpson or the adaptive Lobatto algorithm are presented in a recursive way. The benefit of the recursive programming is the compact and clear representation. However, recursive quadrature algorithms might be transformed into iterative quadrature algorithms without major modifications in the structure of the algorithm.We present iterative adaptive quadrature algorithm (adaptiveSimpson and adaptiveLobatto), which preserves the compactness and the clarity of the recursive algorithms (eg quad, quadv, and quadl) . Our iterative algorithm provides a parallel calculation of the integration function, which leads to tremendous gain in run-time, in general. Our results suggest a general iterative and not a recursive implementation of adaptive quadrature formulas, once the programming language permits parallel access to the integration function. For details the attached PDF file Conrad_08.pdf.)