root_music

minimum spacing between 2 carrier to be orthogonal

用matlab编写的关于天线问题的程序，用于计算细直导线电容(Prepared using matlab antenna problems on the procedures used to calculate the straight fine-wire capacitance)

基于music算法的均匀圆阵方向估计，算法测试好用，可以下载(Uniform circular array direction estimation based on music algorithm. The algorithm is tested well and can be downloaded.)

隐马尔科夫模型是关于时序的概率模型，描述由一个隐藏的马尔科夫链随机生成不可观测的状态随机序列，再由各个状态生成一个观测而产生观测序列的过程。隐藏的马尔科夫链随机生成的状态的序列，称为状态序列；每个状态生成一个观测，而由此产生的观测的随机序列，称为观测序列。马尔科夫链由初始概率分布、状态转移概率分布以及观测概率分布确定(The hidden Markov model is a probabilistic model for time series. It describes the process of randomly generating unobservable state random sequences from a hidden Markov chain, and then generating an observation by each state to produce an observation sequence. A sequence of randomly generated states of hidden Markov chains, called a sequence of states; each state produces an observation, and the resulting random sequence of observations is called an observation sequence. Markov chain is determined by initial probability distribution, state transition probability distribution and observation probability distribution)

File that given the data to cluster and the bandwith returns the number of clusters, its centroids and its distributions

二维经验模态分解的一个程序，改进了插值算法。输入为图像灰度图(A program of two-dimensional empirical mode decomposition and improved interpolation algorithm. Enter the grayscale image)

用不加权的递推最小二乘法进行参数估计，用于系统辩适、仿真(Using non-weighted recursive least squares parameter estimation method for systems dialectical relevance, simulation)

Physical Principles of Sedimentary Basin Analysis源代码和书(Physical Principles of Sedimentary Basin Analysis)

本程序直接摘自文献： ％ S. K. Mitra. Digital Signal Processing: A Computer-Based Approach. Second Edition, ％ McGraw-Hill,2001 清华大学出版社，2001(directly extracted from the literature : S. K. Mitra%. Digital Signal Processing : A Computer-Based Approach. Second Edition. % McGraw-Hill, 2001 Tsinghua University Press, 2001)

提取数据波形时域特征（绝对幅值、平均值、峭度、过零点）并且用LDA分类(Time-domain waveform data extraction features (absolute amplitude, mean, kurtosis, zero crossing) and classification with LDA)