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OFDM在MATLAB仿真软件下的仿真，很有用，很基础，很重要。(OFDM simulation in the matlab. it is very basic code and importent. )

宽带波束形成 倍频程波束形成 恒定束宽波束形成(Broadband Beamforming Beamforming octave constant beamwidth beamforming)

matlb开发的几个仿真例子，以及应用实例和方法。(matlb developed several simulation examples, and application examples.)

how to crack gmat .. learn it the professional way

另外一种QUIN插值频率估计算法。matlab代码(QUIN another interpolation algorithm for frequency estimation. matlab code)

管式固定床反应器瞬态模拟，采用线上求解法(using the online method simulates the transient performances of Tubular fixed bed reactor )

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.)

Matlab script to plot releigh function.

Gonzalez, digital image processing of matlab toolkit

本仿真为电动汽车充电仿真，采用了非隔离式的DC/DC环节(The simulation for the electric car charging simulation, using a non-isolated DC/the DC link)