tulun

cdma的仿真，介绍了CDMA的各种仿真程序，包括信道的仿真，噪声的处理等。(cdma simulation, describes the various CDMA simulation program, including channel emulation, noise processing.)

用于分类的matlab工具箱，供大家学习交流(Matlab toolbox for classification ，We can exchange advices with it.)

这个是专门详细讲解Matlab中的.mat 文件的。(Matlab is designed to explain this in detail. Mat files.)

复合材料的优化,内容里边有很好的描述以及很多的计算实例,适合进阶学习(Objective of this Matlab s program was researched optimization analysis of laminated composite plates for determined the ultimate strength and stress effects of plate s under the regular and uniform out-loads. Therefore, generally Reissner s flat and thick shell finite element model (4Node-20Dof) was developed with first-order shear deformation theory (FSDT). Kirchhoff s classical laminate plate theory yields in adequate results for thick plates (a/th<20). This classical laminated plate (CLPT or CPT), was one of the first developed by Reissner with shear deformation theory. Afterwards, Mindlin was utulizated this shear deformation theory to accommodate rotary of inertia terms on per unit freedom. If this plate system s be very thick (a/th<10) than it is fail to shear deformation-motion and it s condition of adaptive shear stress on plate s top and bottom surface. While this conditions was produced on plate s segment when requered the shear correction factor of shear locking eff)

一种直驱式永磁同步风力发电机组的建模，根据初值确定输出功率。(A model of a direct-drive permanent magnet synchronous wind turbines, according to the initial value to determine the output power.)

Matlab教程-用户图形界面设计gui(matlab gui)

说明：  空间变异函数，可用于土壤中有机质速效磷等的计算(Realization of two-dimensional variation function calculation)

5节点潮流计算，牛顿拉夫逊，如果需要多节点的话，自行改设参数(5-bus power flow calculation, Newton Raphson, if you need multi-node, then re-established parameters of their own)

对波达方向进行估计，通过MUSIC算法估计波达方向，利用MATLAB进行仿真，观察信号相干时MUSIC算法与改进MUSIC算法的比较(Estimation of DOA estimated by MUSIC DOA algorithms using MATLAB simulation, MUSIC MUSIC algorithm and improved algorithm when comparing the observed signal coherent)

Matlab support vector machine training part 2