Matlabshipingfenxi

导师传给我的关于MSK和GMSK的一些相关MATLAB仿真源码，希望对大家有用(Simulation program to realize GMSK transmission system)

等间距线性阵列，阵元数M=8，阵元间距d= λ /2，等幅加权，目标方位φr =0°。产生空间白噪声矢量（复高斯分布）。 设阵列信号矢量元素s(m)=exp[j mψr]，其信号幅度为1，该阵元接收机附加的高斯噪声为n(m)=nmr+jnmi，其中实虚部均为独立同分布N(0, σ2)的高斯随机数，则该通道合成信号x(m)=s(m) + n(m)，其中信噪比为： SNR = 10 lg[1/(2σ2)] = – 3 – 10 lg(σ2) (dB) (The spacing of the linear array, and the array element number M = 8, the array element spacing d = λ/2, equal amplitude weighted target azimuth φR = 0. Space generated white noise vector (complex Gaussian distribution). Let array signal vector elements s (m) = exp [j mψr], the signal amplitude, the element receiver additional Gaussian noise n (m) = nmr+jnmi which the real and imaginary parts are independent and identically distributed N ( Gaussian random numbers of 0, σ2), the channel the synthesis signal x (m) = s (m) the PPLS n (m), where SNR is: SNR = 10 lg [1/(2σ2)] =- 3- 10 lg (σ2) (dB))

matpower安装包和说明使用，非常简单易学(Matpower installation package and instructions are very simple and easy to learn.)

扩展卡尔曼滤波程序，自己在用的，效果还可以，给大家参考下(Extended Kalman filtering procedure)

mfile investigates the generation, transmission and reception of the OFDM signal without channel noise or HPA effect

simulink简明教程，初步了解simulink的使用方式(simulink simple tutorial a preliminary understanding of the usage simulink)

前推潮流算法，非常使用，方便新人学习，常用的潮流计算算法(forward flow algorithm, very used to facilitate new learning, commonly used power flow calculation algorithm)

移相法生成单边带调制信号，对m(t)=sinc^2(t)函数构成的基带信号进行单边带调制,接收端相干解调低通滤波。(ssb_mod_01.m- phase shift method to generate the single sideband modulation signal m (t) = the sinc ^ 2 (t) function constitute the base band signal performs single sideband modulation, the receiving terminal Coherent Solutions of low pass filtering)

低秩矩阵与稀疏表示原理，详细的说明了用低秩矩阵与稀疏表示去分离一个有噪声的图像(The low-rank matrix with sparse principle, a detailed description of the low-rank matrix with sparse to isolate a noisy image)

hybrid Archive-based Micro Genetic Algorithm (AMGA) on a set of bound-constrained synthetic test problems is reported. The hybrid AMGA proposed in this paper is a combination of a classical gradient based single-objective optimization algorithm and an evolutionary multi-objective optimization algorithm.