chap8_4

对m序列的原理、结构、性质进行了分析,在Matlab中采用编程和Simulink动态仿真功能2 种方式实现了m序列.仿真实验表明,这2种方法简单,易于实现,可移植性较强,具有可行性和 设计的合理性. (The principle of the m sequence, structure and properties were analyzed in Matlab, Simulink using dynamic programming and simulation capabilities are 2 ways to achieve the m sequence. Simulation results show that these 2 simple and easy to implement, portability strong the feasibility and rationality of the design.)

说明：  老外的电机学教材，最为重要的是有相应的MAtlab代码，每一章都有，十分详细，学习电机的必备工具书，文件是在太大，此处上传chap6的源码(Foreigners motor learning materials, the most important thing is there is a corresponding MAtlab code, each chapter has a very detailed study of the motor necessary books, documents are too large to upload chap6 source code here)

AWGN channel simulation with Golay coding. Modulation method is BPSK. BER curve is provided.

根据雷达方程计算SNR和R的关系 并有关系图(According to the radar equation the relationship between SNR and R and have the relationship graph)

基于hessian矩阵的图像处理，，内附hessian的matlab源码 (Hessian matrix-based image processingg, matlab source containing the hessian )

有限元刚度矩阵计算有限元刚度矩阵计算有限元刚度矩阵计算(Finite element stiffness matrix computation finite element stiffness matrix computation finite element stiffness matrix calculation)

电力系统仿真，简洁，高效，有三机九节点、14节点、风机、光伏等模型(Power system simulation, simple and efficient)

本文设计了低噪声LNA放大器，较好了达到了指标，但是仍需改进。(This article is designed LNA low-noise amplifier has achieved a good target, but still needed improvement.)

黄金分割法，要用的自己下来看看吧，很好的优化程序 (Golden section method, we should take a look at it from their own, a good optimizer)

[x,f]= L01p_e(c,A,b,N)用枚举法求解下列 0-1线性规划问题min f=c *x, s.t. A*x<=b,x的分量全为整数0或1, 其中N表示约束条件 Ax ≤ b中的前N个是等式，N= 0时可以省略。 返回结果x是最优解，f是最优解处的函数值。 ([X, f] = L01p_e (c, A, b, N) with the following enumeration method for solving linear programming problems 0-1 min f = c ' * x, st A* x < = b, x is an integer of all components 0 or 1, where N represents the constraints Ax ≤ b in the equation of the first N, N = 0 can be omitted. Return result x is the optimal solution, f is the function value at the optimal solution.)