shipinzhuanhuan

光学工程类Matlab模拟程序，模拟了2N个透镜阵列的成像(Optical Engineering Matlab simulation program to simulate a lens array of imaging 2N)

toolbox which campute a constant-Q transform cqt for the music processing.

合成孔径雷达（SAR），正侧视情况下的距离多普勒算法（RDA），多点目标仿真，Matlab语言。(Range Doppler Algorithm of Synthetic Aperture Radar in side_looking using Matlab)

MATLAB CODE FOR SIMULATION OF A SUCCESSIVE APPROXIMATION CONVERTER(MATLAB CODE FOR SIMULATION OF ASUCCESSIVE APPROXIMATION CONVERTER)

basic Pulse width Modulation inverter

Player fills a number from 1 to 9 into given empty space with a rule that no number is appear twice in a single row, column, and minigrid. To play a game of Sudoku, click PlayGame button and an incomplete board of Sudoku will be created in the grid box. Use CheckBoard button to check whether there is a violation in the board. To solve an incomplete Sudoku board, fill the grid box with the corresponding number and click SolveSudoku button. Remember to click ResetBoard before starting a new game or entering an incomplete board to be solved.

kock fractal drawing

試做錄音.讀音訊檔 並做FFT轉換和端點偵測(介面) MATLAB程序(Try to do the recording. Reading audio files and do the the FFT conversion and endpoint detection (interface) MATLAB program)

MATALAB BASEDSIMULATION IN DEC 2014

说明：  共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数。(The Conjugate Gradient method is a method between the steepest descent method and the Newton method. It only needs to use the first derivative information, but overcomes the shortcomings of the steepest descent method and avoids the need for the Newton method to store And the calculation of Hesse matrix and the inverse of the shortcomings, conjugate gradient method is not only to solve large-scale linear equations one of the most useful methods, but also solution for large-scale nonlinear optimization of one of the most effective algorithm. In a variety of optimization algorithms, conjugate gradient method is a very important one. The advantage is that the required storage capacity is small, with step convergence, high stability, and does not require any external parameters.)