MSequence.m

implement linear least square solution to estimating the fundamental matrix

power_thyristor.rar,功率电子领域matlab仿真文件，已经验证过，程序运行正常(power_thyristor.rar.rar,Power electronics field matlab simulation file, has already been verified, the normal operating procedures)

双基地MIMO雷达利用ESPRIT算法实现目标二维方位角联合估计 (The ESPRIT algorithm bistatic MIMO radar goals 2D azimuth joint estimation)

该电子书是matlab/simulink编程开发控制等的最好教材，真是极品，相信你一定会收藏。(The e-book is a matlab/simulink Programming control, the best materials, is really Need, I believe you will collection.)

蓝牙协议语音通信ｍａｔｌａｂ仿真程序，包含语音传输， I/O, CVSD speech coding, HEC, FEC, framing, GFSK Modulation, frequency hopping, 和802.11b interferer.(Simulink model of a Bluetooth communication link transmitting HV1, HV2 or HV3 voice packets. Includes wave file I/O, CVSD speech coding, HEC, FEC, framing, GFSK Modulation, frequency hopping, and an 802.11b interferer.)

静止点目标的距离-多谱勒（R-D）成像算法,有徙动校正模块，根据保铮老师的《雷达成像技术》一书编写，对雷达成像的初学者帮助很大！！(Stationary point target range- Doppler (RD) imaging algorithm, there is migration correction module, according to Bao Zheng teacher radar imaging--a book written for beginners on the radar imaging is very helpful! !)

这本书是老师推荐给我的，非常好，我用这个学习matlab然后毕设时候很顺利。(This book is the teacher recommended to me, very good learning matlab and then completed the set up very well when I use this.)

图像的反转，灰度线性变换，非线性变换，直方图均衡化，中值滤波，梯度算子检测边缘等，，(The reversal of the image, the gray linear transformation and non-linear transformation, histogram equalization, median filtering, edge detection and so on, the gradient operator, )

In this section, the PAPR performance of the proposed algorithms is shown. To evaluate the PAPR performance, the CCDF is employed. The specification detail of simulation parameters is given in TABLE I. In Fig. 5 is shown the PAPR with a PTS method (U = 8) and conventional PTS (U = 4) are improved 4.3 dB and 2.6 dB from ordinary MIMO-OFDM signal when CCDF = 10− 4 respectively and Fig. 6 is shown the PAPR with an optimal PTS method in case of 128 subcarriers.

帝王蝶优化算法,一种新的元启发式优化算法！(In nature, the eastern North American monarch population is known for its southward migration during the late summer/autumn the northern United States and southern Canada to Mexico, covering thousands of miles. By simplifying and idealizing the migration of monarch butterflies, a new kind of nature-inspired metaheuristic algorithm, called Monarch Butterfly Optimization (MBO), a first of its kind, is proposed in this paper. In MBO, all the monarch butterfly individuals are located in two distinct lands viz. Southern Canada & northern United States (Land 1) and Mexico (Land 2). Accordingly, the positions of the monarch butterflies are updated in two ways. Firstly, the offsprings are generated (position updating) by migration operator, which can be adjusted by the migration ratio. It is followed by tuning the positions for other butterflies by means of butterfly adjusting operator. In order to keep the population unchanged and minimize fitness uations, the sum of the newly-generated but)