gaboo

振动工具箱，源代码，有目录及详细说明，希望对大家有用(Vibration toolbox, source code, there are directory and detailed description, in the hope that useful)

电子通信系统的建模与仿真 第8章 扩频通信 仿真 8.1 扩频码相关性的讨论 8.2 扩频通信原理 8.3 扩频通信系统? 8.4 跳频通信系统(Electronic communications system modeling and simulation in Chapter 8 Simulation of spread spectrum communication spread spectrum 8.1 code related discussion 8.2 Principle 8.3 Spread Spectrum Communications Spread Spectrum Communication System ? 8.4 Frequency Hopping Communication System)

Modèle de la machine asynchrone à cage d écureuil dans le repère dq de PARK.

创建一个理想的mixer输入是理想的LO信号和输入信号输出是混合后的信号。(build a ideal mixer the input is ideal LO signal and the input signal.)

CT滤波反投影重建算法，利用卷积计算，利用矩阵计算积分，比较简单的思想(CT reconstruction)

基于非线性动力学、非线性 控制理论、分岔理论等非线性科学的现代分析方法，对倍周期分岔、Hopf 分岔等 进行控制(Modern analytical methods based on nonlinear dynamics, nonlinear control theory, bifurcation theory and nonlinear science of the period-doubling bifurcation, Hopf bifurcation control)

用Matlab编程实现小波变换小波变换的mallat算法，多孔算法，小波提升算法(Programming with Matlab wavelet transform mallat wavelet transform algorithm, porous algorithm, wavelet lifting scheme)

摘要:正交频分复用(OFDM)是第四代移动通信的核心技术。该文首先简要介绍了OFDM基本原理,重点研究了理想同步情 况下,保护时隙(CP)和不同的信道估计方法在高斯信道和多径瑞利衰落信道下对OFDM系统性能的影响。在给出OFDM系 统模型的基础上,用MATLAB语言实现了整个系统的计算机仿真并给出参考设计程序。最后给出在不同的信道条件下,保 护时隙、信道估计方法对OFDM系统误码率影响的比较曲线,得出了较理想的结论。 (O FDM is the key techno logy of 4G in the field of mobile comm unication.In this article O FDM ba sic p rinc ip le is briefly in troduced.Then,the influence of CP and d iffe rent channe l e stim a tion on the system pe rfo rm ance is emp ha tica lly analyzed respectively in Gauss and R ayle igh fading channe ls in the cond ition of ideal synchronization.B e sides,based on the given system mode l O FDM system is compu te r sim u la ted w ith MA TLAB language and the refe rentia l design p rocedure is given.Fina lly,the B ER cu rves of CP and channe l e stim ation a re given and comp ared.The conclusion is sa tisfac to ry. )

用多尺度卡尔曼滤波法，对信号参数进行识别估计。高频信号和低频信号识别结合起来改进了算法识别的精确度和准确度。(It is an implementation of hierarchical (a.k.a. multi-scale) Kalman filter using belief propagation. The model parameters are estimated by expectation maximization (EM) algorithm. In this implementation, we considered two time series with different frequencies. The messages between high and low frequency signals are combined to improve the estimation and prediction.)

this is extended euclid source code