Matlab--code-of-SINS

一种BCH码编译码的实现 一种用可编程逻辑器件和单片机实现BCH码编、译码的方案(Encoding and decoding a BCH code with the realization of a single-chip programmable logic devices and for the realization of BCH codes, decoding of the program)

基于matlab GUI界面设计,可以动态调节运行环境的参数，详细画出了时域和频域的相关图，一种流形学习算法（很好用），结合PCA的尺度不变特征变换(SIFT)算法，用于建立主成分分析模型，实现了对10个数字音的识别程。( Based on matlab GUI interface design, Can dynamically adjust the parameters of the operating environment, Correlation diagram shown in detail the time domain and frequency domain, A fluid manifold learning algorithm (good use), Combined with PCA scale invariant feature transform (SIFT) algorithm, Principal component analysis model for establishing, Realization of 10 digital audio recognition progra.)

一个GUI程序，可输入数据和公式进行绘图(a GUI procedures, data entry and mapping formula.)

这是最简洁，注释得最好的HOG(Histogram Oriented Gradient)算法的matlab实现。可用于行人识别和物体跟踪。(This code is well commented, which enables the adjusting of the HOG parameters. This code was developed for the work: O. Ludwig, D. Delgado, V. Goncalves, and U. Nunes, Trainable Classifier-Fusion Schemes: An Application To Pedestrian Detection, In: 12th International IEEE Conference On Intelligent Transportation Systems, 2009, St. Louis, 2009. V. 1. P. 432-437.)

运用Matlab进行分类、参数估计和状态分析(Classification, parameter estimation and state estimation- An engineering approach using Matlab)

很不错的目标跟踪轨迹模拟MATLAB仿真程序，可以在MATLAB0.7运行成功(Good target tracking trajectory simulation of MATLAB simulation program, can run in MATLAB0.7 success )

含噪的三角波和正弦三角波去噪问题，简便的程序，直接在matlab中打开即可(meaningful)

自适应滤波LMS算法和bp算法，解决一些基本数学问题(Adaptive filtering LMS algorithm and the bp algorithm to solve basic math problems)

数学里的免疫算法，利用matlab编制的(Immune algorithm)

经验模态分解方法简称EMD方法。该方法从本质上讲是对一个信号进行平稳化处理，其结果是将信号中真实存在的不同尺度波动或趋势逐级分解开来，产生一系列具有不同特征尺度的数据序列。(Empirical mode decomposition method is referred to as the EMD method. This method is in essence a signal smoothing processing, the result is the real signal different scales swings or trends gradual decomposition open, resulting in a series of a data sequence having a different characteristic scale.)