GM11

说明：  矩阵LDLT分解与Cholesky分解 求矩阵A=（αij）20x20的LDLT分解与Cholesky分解(Matrix LDLT decomposition and Cholesky decomposition Matrix A = (αij) 20x20 of the LDLT decomposition and Cholesky decomposition)

After identifying the best MNT− 1 nodes with the simplified branch metric and the accumulated branch metric at stage NT − 1, we then calculate the LLR of each coded bit utilizing the standard squared Euclidian distance metric. The log-likelihood ratio (LLR) of a posteriori probability (APP) of each coded bit conditioned on the received signal y is normally calculated using the max-log approximation.

《MATLAB时尚百例实例》实例1-13()

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.)

A function to evaluate a neural nets performance as called from the PSO function

The M-file generates modulated signals using BPSK, QPSK, 16QAM and 64QAM modulation.

fibonacci search method optimization methods and algortihms

齿轮箱故障诊断实用技术，可以有效掌握齿轮箱具体的故障诊断方法和步骤。(Practical gear box fault diagnosis technology, can effectively grasp the gearbox fault diagnosis methods and steps of the specific. )

N个小球的电磁散射，只有偶极子点的相互作用(Scattering by N Small Spheres, dipole point interactions only)

直流电动机的机械特性，很有用的，MATLAB仿真(DC motor mechanical properties, very useful, MATLAB simulation)