6.-LP-Example-6-Diet-Problem

Harris采用了一种新的角点判定方法。矩阵M的两个特征向量l1和l2与矩阵M的主曲率成正比。Harris利用l1, l2来表征变化最快和最慢的两个方向.若两个都很大就是角点,一个大一个小就是边缘,两个都小就是在变化缓慢的图像区域.(Harris adopted a new method of determining the corner. Matrix M of two feature vectors l1 and l2 with the matrix M is proportional to the principal curvatures. Harris use l1, l2 to characterize changes in the fastest and slowest in two directions. If both are great that corner, a little is a big edge, both small change is slow in the image area.)

crossover mutation encode

1. BPSK modulation of data which ever you input (default data is “MANIPAL REDDY”). 2. MANIPAL REDDY is changed into ASCII Format and into two-bit format for BPSK Modulation. 3. Chaos is used for spreading the binary bit sequence. 4. Uniformly distributed Noise is added to Spread signal. 5. After reception Chaotic Chip sequence is used to recover message . 6. Filter is used for removing spikes and noise. 7. Note the filter is used is just for showing a little realisitic picture. 8. Appropriate filter should be used. 9. The original data in binary and recovered data in binary format are compared

单小区单用户多天线MIMO环境下，QPSK调制进行MMSE接收处理，比对理想，非理想和一般MMSE接收的性能(Under the single-cell single-user multi-antenna MIMO environment, QPSK modulation MMSE receiving treatment, compared to the ideal, non-ideal performance and general MMSE reception)

linear acceleration

瑞利信道MATLAB实现，基于matlab的源代码(Rayleigh Road MATLAB implementation, based on the source code matlab)

This is the map with all the matlab codes used by group D28

zero crossing feature extraction

this is clipping code for papr reduction in matlab.In this code clipping is fillowed by filtering to reduce inband interference.Simulated results are in the form of graphs to compare performance

课程设计中实现matlab的最优化设计，程序代码包括各种算法，如最速下降法 共轭梯度法，牛顿法，修正牛顿法，拟牛顿法，信赖域法，显式最速下降法， MDOMxw梯度投影法，修正G－N法，基本粒子群算法，带压缩因子的粒子群算法，权重改进的粒子群算法，ZMGGiit二阶粒子群算法等等。 (Curriculum design to achieve matlab optimization design, program code includes a variety of algorithms, such as the steepest descent method conjugate gradient method, Newton s method, modified Newton method, quasi-Newton method, trust region method, explicitly steepest descent method, MDOMxw gradient projection law, amendment G-N method, particle swarm algorithm, particle swarm algorithm with compression factors, weights improved particle swarm optimization, ZMGGiit second-order particle swarm optimization and so on. )