fourier

求解多元函数问题，将其转化为求极值问题，用matlab求解。(solve the Max or min)

february series code

Bairstow案例，主要是以matlab軟件來運算標準題型。(Bairstow cases, mainly matlab software to compute the standard questions.)

说明：  有源滤波器（APF）matlab_simulink仿真图的子图之一。算法是DQ0 算法。(active filter (APF) matlab_simulink simulation map one of the graph. The algorithm is DQ0 algorithm.)

说明：  利用FFT快速算法来实现二维图像基于匹配追踪算法的稀疏分解。(Fast Algorithm for the use of FFT to achieve two-dimensional image matching tracking algorithm based on sparse decomposition.)

经优化后的xls文件导入到dbf文件的表单,dbf文件请自己创建(By importing the XLS file after the optimization to the DBF file form, please create your own DBF file )

一種可用於SAR影像上的應用，並且提供使用者簡單的把圖片慮波得到更好的影像辨識(An application can be used on the SAR images, and provides users with a simple wave to get a better picture into account image recognition)

Multi Layer Perceptron implementation

自己做设计用的参数提取程序，主要是LPCC和MFCC。(Designs its own program with the parameter extraction, mainly LPCC and MFCC.)

The cable compensation system is an experiment system that performs simulations of partial or microgravity environments on earth. It is a highly nonlinear and complex system.In this paper, a network based on the theory of the Fuzzy Cerebellum Model Articulation Controller(FCMAC) is proposed to control this cable compensation system. In FCMAC ,without appropriate learning rate, the control system based on FCMAC will become unstable or its convergence speed will become slow.In order to guarantee the convergence of tracking error, we present a new kind of optimization based on adaptive GA for selecting learning rate.Furthermore, this approach is evaluated and its performance is discussed.The simulation results shows that performance of the FCMAC based the proposed method is stable and more effective. (The cable compensation system is an experiment system that performs simulations of partial or microgravity environments on earth. It is a highly nonlinear and complex system.In this paper, a network based on the theory of the Fuzzy Cerebellum Model Articulation Controller (FCMAC) is proposed to control this cable compensation system. In FCMAC, without appropriate learning rate, the control system based on FCMAC will become unstable or its convergence speed will become slow.In order to guarantee the convergence of tracking error, we present a new kind of optimization based on adaptive GA for selecting learning rate.Furthermore, this approach is evaluated and its performance is discussed.The simulation results shows that performance of the FCMAC based the proposed method is stable and more effective.)