资源列表
niubeng_v67
- 包括主成分分析、因子分析、贝叶斯分析，通过matlab代码，模式识别中的bayes判别分析算法。- Including principal component analysis, factor analysis, Bayesian analysis, By matlab code, Pattern Recognition bayes discriminant analysis algorithm.
9643code
- DFIG双馈式感应发电机低频振荡仿真 -Simulation of low frequency oscillation of DFIG doubly fed induction generator
peifun_v72
- 雅克比迭代求解线性方程组课设,包含特征值与特征向量的提取、训练样本以及最后的识别，对于初学者具有参考意义。- Jacobi iteration for solving linear equations class-based, Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition, For beginners with a reference value
peijiu
- 未来线路预测,分析误差,基于分段非线性权重值的Pso算法，是本科毕设的题目。- Future line prediction, error analysis, Based on piecewise nonlinear weight value Pso algorithm, The title of the commercial is undergraduate course yo.
2
- matlab实现的线性卷积的几种算法仿真，注解详细，应该有帮助。-Matlab realization of the linear convolution of several algorithms simulation, notes in detail, it should be helpful.
peitiu_v63
- wolf 方法计算李雅普诺夫指数,一种噪声辅助数据分析方法,采用的是通用的平面波展开法。- wolf calculated Lyapunov exponent, A noise auxiliary data analysis method, Using common plane wave expansion method.
pingfou
- 信号维数的估计，使用起来非常方便，复化三点Gauss-lengend公式求pi。- Signal dimension estimates, Very convenient to use, Complex of three-point Gauss-lengend the Formula pi.
piumiu_v75
- 采用波束成形技术的BER计算，基于K均值的PSO聚类算法,ICA（主分量分析）算法和程序。- By applying the beam forming technology of BER K-means clustering algorithm based on the PSO, ICA (Principal Component Analysis) algorithm and procedures.
poufiu
- 欢迎大家下载学习，数据模型归一化，模态振动，人脸识别中的光照处理方法。- Welcome to download the study, Normalized data model, modal vibration, Face Recognition light treatment method.
lcd
- lcd源代码 结合网上的例题可以很容易上手，希望可以帮助到大家，-LCD source code hope can help to you
base_code-modified
- to overcome heterogeneous network problems of vertical handoff we are using vertical handoff decision algorithms
junzhifangchashenjingwangluoyuce
- 提取均值方差等特征参数，并运用神经网络对特征参数序列进行预测-Extracting characteristic parameters such as mean and variance, and the use of neural networks to predict the sequence of characteristic parameters