Lqrsim

文章中主要阐述了PN码的捕获，并对以前的各种捕获方法进行了改进。得出了基于FFT的快速捕获算法！(Abstract-A FFT-based parallel acquisition algorithm for Direct Sequence/Spread Spectrum radio navigation system is studied to solve long PN code acquisition using serial method. Frequency domain analysis of FFT to acquire signal is applied in this paper and state transfer function is used to derive the expression of average acquisition time.)

分析非平稳时变的实证分解法（EMD）的基础上产生的适应性，本征模函数（IMF）的数据，处理的数据。(analyze the non-stationary time-varying data processed by the Empirical Decomposition Method (EMD), which generates the adaptive basis, Intrinsic Mode Functions (IMF), from the data. Each chapter package name (or directory) is specified in parentheses. )

小波去噪的MATLAB源程序，希望对大家有帮助！(Wavelet Denoising MATLAB source code, I hope all of you help!)

avo_abe - AVO intercept and gradient attributes for P-P and P-S

关于电力系统负荷预测用matlab语言编程方面的论文。(About power system load forecasting matlab language programming papers.)

精通MATLAB计算科学书源代码，原书正版CD第二章源代码(Proficient in computer science book MATLAB source code, the original book source code CD to Chapter)

对carmaker软件进行了介绍，对汽车仿真有很大的帮助，促进汽车的生产。(Software for the carmaker introduced, car simulation of great help to promote the production of cars.)

本程序特别适合于弹道计算等方面使用。比ODE45函数的速度加快了很多，且程序充分展示了Matlab向量运算的强大功能，以及编程的简单快捷。(This procedure is particularly suitable for use ballistic calculations and other aspects. ODE45 faster than a lot of functions and procedures for demonstrating the power of Matlab vector operations, and programming simple and quick.)

多维数据分析,有nPLS,PARAFAC,TURKER等(multidimensional data analysis, nPLS, B6, and other TURKER)

A. Fusion at the Feature Extraction Level The data obtained from each sensor is used to compute a feature vector. As the features extracted from one biometric trait are independent of those extracted from the other, it is reasonable to concatenate the two vectors into a single new vector. The primary benefit of feature level fusion is the detection of correlated feature values generated by different feature extraction algorithms and, in the process, identifying a salient set of features that can improve recognition accuracy [14]. The new vector has a higher dimension and represents the identity of the person in a different hyperspace. Eliciting this feature set typically requires the use of dimensionality reduction/selection methods and, therefore, feature level fusion assumes the availability of a large number of training data.