Multi-objective-particle-swarm

说明：  该程序用matlab实现求两直线的交点，显示直线和交点坐标。(Present two lines intersection)

林智仁教授的lib-svm直接解压到matlab文件夹下即可使用。(Unzip lib-svm professor Lin Zhiren under the MATLAB folder can be used. )

通过步进频率技术进行带宽合成，通过脉冲压缩，验证先压缩与后压缩的区别。结果表演，压缩后拼接与拼接后压缩效果一致。(Through the step frequency technology for the synthesis of bandwidth, through the pulse compression, verify the compression sequence don t affect the result of bandwidth synthesis.)

说明：  FA算法，能很好的解决函数优化问题，对于解高维函数有较好的实验结果(FA algorithm can solve function optimization problem, the solution of high-dimensional function for better results)

基于模糊控制的PID温度控制器的设计 :将模糊控制和PID 控制相结合起来，通过模糊控制实现PID 参数自适应的方法来控制系统温度。这种Fuzzy- PID 策略，模糊控制的采用不是代替PID 控制，而是对传统控制方式的改进和扩展，它既保持了常规PID 控制系统结构简单、使用方便、鲁棒性强、控制精度高的优点，又采用模糊推理的方法实现了PID 参数PK、IK、DK的在线自整定，兼具了模糊控制灵活性、适应性强的特点，相比单纯的任一种控制效果都要好(PID temperature controller design based on fuzzy control: fuzzy control and PID control combine to achieve PID adaptive approach to control system temperature by means of fuzzy control. This Fuzzy- PID strategy is not to replace the use of fuzzy control PID control, but the traditional control methods to improve and expand, both to maintain a simple and conventional PID control system structure, easy to use, robust, and high control accuracy advantages, but also the use of fuzzy inference PID parameters to achieve the PK, IK, DK-line self-tuning, both the fuzzy control flexibility, adaptability features, compared to simply have a good control effect either)

对不同区域进行断面分析，并让图片生成在一张图上(Cross-section analysis for different areas and let the picture generated a map)

应用多元高斯声束叠加方法建立粉末合金构件的声场模型(sound field simulation sound field simulation sound field simulation )

说明：  分别用窗函数法和等波纹最佳一致逼近法分别对FIR数字滤波器进行设计和仿真，并通过具体实例进行实现(respectively window function method and the best Bellows were consistent approximation of FIR digital filter design and simulation , and through concrete examples for achieving)

单色发散光束经透射型布拉格光栅的特性的matlab仿真图示(Monochromatic divergent beam transmission Bragg grating characteristics)

卡尔曼滤波器的操作包括两个阶段:预测与更新。在预测阶段,滤波器使用上一状态的估计,做出对当前状态的估计。在更新阶段,滤波器利用对当前状态的观测值优化。(Kalman filter operation consists of two stages: prediction and update. In the prediction stage, the filter is estimated using the previous state, to make an estimate of the current state. In the update phase, the filter use observations on the current state of the optimization.)