TimeFrequencydistribution

交点 matlab(Nodal matlab)

由MLS产生Gold码序列,<通信原理与Matlab仿真>经典范例(MLS generated by Gold code sequences, Communication Theory and Matlab simulation> classic example of)

De Smedt et al 2005, Analytical Solution for transient storage modeling

基于maltab的fm调制系统的设计 含有各种信噪比的调制(The fm modulation system based on maltab design contains a variety of signal to noise ratio of the modulation)

newton raphson MATLAB PROGRAMME

based on within-class inter-class distance criteria, feature extraction. ... in the Yale face database for face recognition on the matlab source

buck converter using the matlab .mdl file for basic learners

说明：  利用粒子群算法优化svm参数，得到高精度的svm模型(The parameters of SVM are optimized by particle swarm optimization (PSO), and the SVM model with high precision is obtained)

对输入的语音信号进行分帧处理，低通滤波，中心削波，求自相关函数最后得到基音轨迹。(Speech input signal framing processing, low-pass filtering, center clipping, seeking autocorrelation function finally got the pitch trajectory.)

多目标优化 相对传统多目标优化方法, PSO在求解多目标问题上具有很大优势。首先, PSO的高效搜索能力有利于得到多目标意义下的最优解 其次, PSO通过代表整个解集的种群按内在的并行方式同时搜索多个非劣解,因此容易搜索到多个Pareto 最优解 再则, PSO的通用性使其适合于处理所有类型的目标函数和约束 另外, PSO 很容易与传统方法相结合,进而提出解决特定问题的高效方法。就PSO 本身而言,为了更好地解决多目标优化问题,必须解决全局最优粒子和个体最优粒子的选择问题(Compared with the traditional multi-objective optimization of multi-objective optimization method, PSO in solving multi-objective problem has a great advantage. First, PSO is conducive to the efficient search capabilities are more objective sense of the optimal solution Secondly, PSO representative of the entire solution set through the population by way of the inherent parallel search multiple non-inferior solution, and this can easily search for the most number of Pareto optimal solution Furthermore, PSO' s versatility make it suitable for handling all types of objective function and constraints addition, PSO is easy to integrate with the traditional method, and then propose an efficient way to solve specific problems. The PSO itself, in order to better address the multi-objective optimization problems, the need to address the global best particle and the individual selection of the optimal particle)