concreteBone

we study the resource allocation problem for the multiuser orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems with proportional rate constraints.

实现了几何多视的功能，这是一个很不错的matalab语言实现的工具箱，包含几十个函数。(achieve more as a geometric function, which is a very good matalab language toolkit, Function contains dozens.)

基于MATLAB的椭圆型方程有限查分法求解源代码(MATLAB based on the elliptic equation method for solving the limited search source code)

The architecture of this set of codes and the interaction among them is shown in Figure 1. The main testing code main code.m calls the code riemann grad unit opt.m that performs Riemannian optimization under unitary matrix constraint. Steepest Descent/Ascent (SD/SA) algorithm (see Table 3.2 in [1]), Conjugate Gradient (CG-PR, CG-FR) algo- rithms (both Fletcher-Reeves and Polak-Ribi`ere formulas, see Table 3.3 in [1]), are im- plemented. This code further calls the codes implementing line search methods: Armijo method geod search armijo.m, as well as the polynomial and DFT-based approximation

Principal component analysis (PCA) is a popular tool for linear dimensionality reduction and feature extraction. Kernel PCA is the nonlinear form of PCA, which is promising in exposing the more complicated correlation between original high-dimensional features. In this paper, we first talk about the basic ideas of PCA and kernel PCA, and then focus on the reconstruction of pre-images for kernel PCA. We also give an introduction on how PCA is used in active shape models (ASMs), and discuss how kernel PCA can be applied to improve traditional ASMs. Then we show some experiment results to compare the performance of kernel PCA and traditional PCA for pattern classification. We also implement the kernel PCA-based ASMs, and use it to construct human face models.

LTE下行链路空分复用闭环。仿真配置：16QAM调制、1/3码率Turbo编码、10MHz带宽、每个子帧一个PDCCH符号、单码字，8次迭代Turbo译码、早期终止机制、MMSE（最小均方误差）MIMO接收器，PDSCH发射端进行空分复用预编码。信道模型是LTE-MIMO信道附加AWGN信道。(LTE downlink closed loop space division multiplexing. Simulation Configuration: 16QAM modulation, 1/3 rate Turbo code, 10MHz of bandwidth, one PDCCH per subframe symbol, single code word, 8 Turbo decoding iterations, early termination mechanisms, the MMSE (minimum mean square error) the MIMO receivers, PDSCH transmitting terminal space division multiplexing precoding. Channel model is LTE-MIMO channel additional AWGN.)

B-M 算法的matlab实现 密码学中又一重要的算法实现(BM algorithm matlab achieve another important cryptography algorithm implementation)

svm 核函数的选择与构造 在matlab中运行(svm kernel function and structure of the choice to run in matlab)

模糊算法PID控制器参数再线自动整定MATLAB程序(Fuzzy PID controller then automatically tuning MATLAB)

classes.mat和classes.mat中存放10个对象人脸的20个7阶不变矩特征，TargetTest.m是构造神经网络对人脸进行识别，再利用DS证据理论进行融合识别(Nerual Network and Fusion Recognition)