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matlab从入门到精通第11章书后源码对初学者很有帮助(matlab)

多径理解3,理解多径对信号的影响 ,(three multi-path understanding, understanding of the multi-path signals and understanding of the multi-path signals,)

一个用于自然数编码遗传算法的工具包indexGA，以及用这个工具包实现的车辆路径优化问题的算法例程(One for the natural number-coded genetic algorithm toolkit indexGA, and use this tool kit to achieve VRP algorithm routine)

多维非线性辨识的MATLAB程序（用神经网络学习二维非线性函数）(multidimensional nonlinear identification MATLAB (using neural networks to learn two-dimensional nonlinear function))

time difference of arrival application for wireless sensor networks

说明：  2BP神经网络的非线性系统建模-非线性函数拟合(bp neural networing)

traveling saleman problem的代码(traveling saleman problem code)

denoise In BayesShrink[5] we determine the threshold for each subband assuming a Generalized Gaussian Distribution(GGD) . The GGD is given by GG¾ X ¯ (x) = C(¾ X ¯ )exp¡ [® (¾ X ¯ )jxj]¯ (6) ¡ 1 < x < 1 ¯ > 0, where ® (¾ X ¯ ) = ¾ ¡ 1 X [ ¡ (3=¯ ) ¡ (1=¯ ) ]1=2 and C(¾ X ¯ ) = ¯ ¢ ® (¾ X ¯ ) 2¡ ( 1 ¯ ) and ¡ (t) = R1 0 e¡ uut¡ 1du. The parameter ¾ X is the standard deviation and ¯ is the shape parameter It has been observed[5] that with a shape parameter ¯ ranging from 0.5 to 1, we can describe the the distribution of coefficients in a subband for a large set of natural images.Assuming such a distribution for the wavelet coefficients, we empirically estimate ¯ and ¾ X for each subband and try to find the threshold T which minimizes the Bayesian Risk, i.e, the expected value of the mean square error.

各向同性等向硬化弹塑性材料，在已知应变的条件下计算应力(Stress update algorithm for a uniaxial elastoplastic material with isotropic hardening)

说明：  通信信号的调制信息包含在信号的瞬时幅度、相位、频率的变化之中，不同的信号其频谱也呈现不同的特征，通过提取瞬时幅度、相位、频率以及频谱的参数统计特征，可以识别不同的通信信号。通常是利用对瞬时幅度、瞬时相位，瞬时频率和信号功率谱进行某种变换而得到可以明显区分各种信号的特征参数。(Communication signal modulation information is contained in the signal instantaneous amplitude, phase, frequency changes, the spectrum of different signals also show different characteristics, by extracting the instantaneous amplitude, phase, frequency and statistical characteristics of the parameters of the spectrum, you can identify different communication signals. Usually by the use of instantaneous amplitude, instantaneous phase, instantaneous frequency and signal power spectrum a transformation which can be clearly distinguished by the characteristic parameters of various signals.)