chapter42

Source code in matlab of neural network.

说明：  design TCP/AQM router using robust control

octive 斯坦福大学公开课 机器学习公开课作业1(octive machine learning publicly Homework1)

In mathematics, the discrete-time Fourier transform (DTFT) is one of the specific forms of Fourier analysis. As such, it transforms one function into another, which is called the frequency domain representation, or simply the "DTFT", of the original function (which is often a function in the time-domain).(This file includes matlab source code about DTFT and also includes explanation report)

Heat equation with variable coeficients using Succesive Over Relaxation

雷达信号瞬时自相关处理，计算信号瞬时频率，计算雷达信号参数等(instant auto-corelation)

matlab匹配的匹配算法，可以调节参数(matching matching matlab)

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.)

一个基于matlab平台关于图像检索的小型GUI！！！(A matlab-based image retrieval on a small platform GUI! ! !)

锚杆挡墙的立柱和锚杆内力的有限元分析,可以分析立柱在挡墙土压力作用下的挠曲线，以及内力大小，对于锚杆挡墙的优化设计具有较大作用。(FEM analysis on the internal forces and deflection of beam for anchoring retaining wall)