femtruss

matlab中遗传算法的源码，简单易懂，学习用很不错(M code of genetic algorithm in matlab)

Estimation of direction in degree for doa study

说明：  传感器网络经典算法 目标减少传感器网络节点能耗(Classical algorithm of sensor network)

多径无线信道在时域的建模仿真，很有参考价值(Multi-path wireless channel modeling in the time domain simulation of great reference value)

2012和2013年关于北京天气统计用于功率负载等分析(related content u know)

统计信号处理：非高斯信号处理及其应用，对非高斯信号的处理及应用作出了详细的讨论。(Statistical Signal Processing: non-Gaussian signal processing and its applications, processing and application of non-Gaussian signal given a detailed discussion.)

说明：  material property for RCWA calculation

How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments. (How the K-mean Cluster workStep 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (Nk) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3. Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4. Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.)

本文講述了一個基於FAN4800 連續PFC 前端的雙管正激電源的功率級設計。回顧了這種電源的設計選擇。討論的實際課題包括功 率器件選型，電磁設計，佈局和電磁干擾 (EMI)，目的在於幫助工程師加速並改善其設計。(This article about a front-end based on the FAN4800 PFC consecutive two-transistor forward power stage power supply design. Review this power supply design options. The actual topics discussed include the selection of power devices, electromagnetic design, layout, and electromagnetic interference (EMI), designed to help engineers to speed up and improve its design.)

说明：  地统计学中基于空间变异原理的差值分析，做空间分析的好材料。matlab实现(To statistical theory based on spatial variability of the difference analysis, a good material to do spatial analysis. matlab implementation)