bianzhi

说明：  用人工鱼群算法实现旅行商问题以及求解极值问题，是一种仿生物行为优化算法(Algorithm using artificial fish solving the traveling salesman problem and extremal problems, is an imitation of biological behavior of optimization)

MR damper control of structures

基于卡尔曼滤波实现雷达目标跟踪算法，MATLAB环境实现(Kalman filter based radar target tracking algorithm, MATLAB environment to achieve)

基于matlab 编写的流体计算和传热程序 包括11个程序(matlab CFD )

MIMO信道容量仿真程序,包括SIMO.MISO.MIMO.SISO几种信道容量的仿真程序(MIMO channel capacity simulation program, including several channel capacity SIMO.MISO.MIMO.SISO simulation program)

The model consists of two systems, a climate control system and an electrical system. This allows for examination of the loading effects of the climate control system on the car s electrical system.

基于Radon变换提出了一种新的图像识别方法，首先构造了二维图像在Radon变换空间的平移和比例 不变量，然后根据变换空间数据的特性，利用奇异值分解得到了旋转不变量并将其用于三类飞机的识别，仿真结果表明该方法具有很好的性能和较高的实用价值。(I nt hisp aper,a n ewi mager ecognitionm ethodb asedo nR adont ransform isp roposed,2一Di magem omentin variant basedo nR adontr ansformi sc onstructed.A ccordingto t hed atain t hetr ansforms pace,Si ngularV alueD ecomposition(SV D)i s proposedh ereto o btainr otationi nvariant.Si mulationr esultsa reg ivent oo btaini nsightin tot hee fficiencieso fferedb yo urm ethod)

使feasp方法用求解线性矩阵不等式的程序，很完整，有注释，对于学习求解线性矩阵不等式很有帮助(Methods to feasp procedures for solving linear matrix inequalities, it is complete, with annotations, for learning useful for solving linear matrix inequalities)

说明：  利用matlab仿真软件仿真SVPWM的波形，例子中有这个实例的解决过程(Matlab simulation using SVPWM waveform simulation software, examples in the process of resolving this instance)

The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorithm can be interpreted as an efficient stochastic mixture of Kalman filters. The software also includes efficient state-of-the-art resampling routines. These are generic and suitable for any application.(The software implements particle filteri Vi and Rao Blackwellised particle filtering az r conditionally Gaussian Models. The RB algori thm can be interpreted as an efficient stochast ic mixture of Kalman filters. The software also includes efficient state-of-the-art resampl ing routines. These are generic and suitable az r any application.)