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：探索一种能有效抑制和消除颅脑MRI运动伪影产生的方法，以提高图像质量和工作效率。方法：利用包装CT管球的海绵，设计并制作了2 cm x 7．5 cm x 22 cm，3 cm x 7．5 cm x 22 cm，4 cm×7．5 cm x 22 em等3种规格的海绵垫， 配合使用颅脑正交线圈进行颅脑MRI检查。结果：采用“加垫法”行颅脑MRI检查2 638例。其中，一次性扫描成功2 633 例(占99．81％)，失败5例(占0．19％)； 在扫描失败的5例患者中，第2次扫描时配合使用医用绷带成功4例。失败l例。结论：采用“加垫法”行常规颅脑MRI扫描，方法简单、可靠。可有效抑制和消除运动伪影的产生，提高图像质量和工作效率。(To explore a brain can effectively inhibit and eliminate motion artifacts of MRI approach to improve the image quality and efficiency. Methods: The CT tube packing sponge ball, designed and made 2 cm x 7.5 cm x 22 cm, 3 cm x 7.5 cm x 22 cm, 4 cm × 7.5 cm x 22 em 3 sizes, etc. sponge pad, with the quadrature head coil using brain MRI. Results: The " plus cushion Law" the Brain MRI examination 2 638 cases. Among them, the one-time scan is successful 2 633 cases (99.81 ), failed in 5 cases (0.19 ) Conclusion: " plus cushion Law" routine brain MRI scan, the method is simple and reliable. Can effectively suppress and eliminate motion artifacts, and to improve image quality and efficiency.)

采用离散余弦变换DCT，通过MATLAB实现数字水印（包括水印的嵌入和盲提取）。( Uses discrete cosine transformation DCT, realizes the digital watermark through MATLAB (including watermark inserting and blind extraction). )

说明：  Genetic Algorithm for solve\ing 2degree Equation

to generate FFt of a semiconductor laser with optical feedback

驱动力行驶阻力平衡图可以求出汽车行驶最大速度(The equilibrium diagram of the running resistance of the driving force can be calculated maximum speed of the vehicle traveling)

Calculated Powers in 3 Phase

kalman滤波，扩展的kalman滤波（EKF），unscented Kalman filter（UKF），基于EKF和UKF混合模型的IMM实现，以及配套的Rauch-Tung-Striebel和two-filter平滑工具，一个很好用的框架(Kalman filtering, extended Kalman filtering (EKF), unscented Kalman filter (UKF), IMM implementation based on EKF and UKF hybrid models, and supporting Rauch-Tung-Striebel and two-filter smoothing tools, a very useful framework)

说明：  二维的仿真，入射波为空间高斯型，入射到一个单狭缝上透射情况。金属介质为Drude模型(Two-dimensional simulation, the spatial Gaussian incident wave, incident to a single slit on the transmission case. Medium for the Drude model of metal)

Matlab implementation for classic kalman filter predicting linear motion.

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