ofdm

说明：  基于压缩感知中DCT基的BP算法，用基追踪算法重构原始信号(Perception-based compression algorithm for DCT based BP, with the basis pursuit algorithm to reconstruct the original signal)

对matlab的使用就行了简单的介绍，通过该文档熟悉对matlab编程的操作以及在各个方面的应用。(Use of matlab' s a brief introduction on the line through the document familiar to matlab programming in all aspects of operation and applications.)

Linear Regression-the effect of feature renormalization

说明：  fastica实测数据，可以做数据的预处理，保留有用信号，滤除噪声(FastICA measured data, can do data preprocessing, retain useful signal, filter noise)

运用matlab进行下个点的预测分析，并画出了预测误差示意图(use Matlab for the next point forecasts and analysis, and the mapping out of the prediction error Map)

matlab的电力电子建模,电力电子变换器simulink 建模(power and electronic modeling using matlab)

Report and thesis on abnormal crowd detection.

f16横侧向特征跟配置控制设计和LQR最优控制设计(F16 the eigenvalues of the horizontal lateral configuration and LQR optimal control design)

Advanced correlation filter synthesis algorithms to achieve rotation invariance are described. We use a specified form for the filter as the rotation invariance constraint and derive a general closed-form solution for a multiclass rotation-invariant filter that can recognize a number of different objects. By requiring the filter to minimize the average correlation plane energy, we produce a multiclass rotation invariant (RI) RI-MACE filter, which controls correlation plane sidelobes and improves discrimination against false targets. To improve noise performance, we require the filter to minimize a weighted sum of correlation plane signal and noise energy. Initial test results of all filters are provided

The Cross Bilateral filter can enhance the PSNR of multi focus images that is in image fuison. Bilateral filtering is a local, nonlinear and non- iterative technique which combines a classical low-pass filter with an edge stopping function that attenuates the filter kernel when the intensity difference between pixels is large. As both gray level similarities and geometric closeness of the neighboring pixels are considered, the weights of the filter depend not only on Mahalanobis distance but also on the distance in gray/color space. The advantage of the filter is that it smoothes the image while preserving edges using neighboring pixels. CBF considers both gray-level similarities and geometric closeness of neighboring pixels in image one to shape the filter kernel and filters the image two.