gsd_OFDMA_schedule

对混沌时间序列相空间重构中最佳延迟时间间隔和嵌入维数的选取方法作 了综述,提出了同时考虑这2 个参数选取的重构展开虚假邻点法以及预测误差最小(Of chaotic time series phase space reconstruction of the best delay time interval and the embedding dimension of the selection methods were reviewed and put forward these two parameters taking into account the reconstruction of the selected start-point method of false neighbors, as well as the minimum prediction error)

共包含四个文件： hamo_packet.m 谐波小波包子程序，输入参数为原信号序列，采频，分解层数，返回三维数组，存储各层各频带分解结果； harmopacktest.m 检验上述子程序可行性的m文件； harmonic wavelet analysis.pdf Newland关于谐波小波的原始论文； 20130329谐波滤波.docx 内附matlab程序和分析结果。对电机电流信号做了谐波小波分解，分别从时域和频域构造谐波小波，结果显示，频域构造的小波光滑性稍差。(Contains four files: hamo_packet.m harmonic wavelet buns procedures, input parameters as the original signal sequence mining frequency decomposition level, return to the three-dimensional array, storage layers each band decomposition results harmopacktest.m test subroutine feasibility m-file harmonic wavelet analysis.pdf Newland original papers on harmonic wavelet 20,130,329 harmonic filter the. docx included matlab program and analysis of the results. Harmonic wavelet decomposition of the motor current signal, respectively, from the time domain and frequency domain construct harmonic wavelet, the results show that wavelet smoothing a less frequency-domain structure.)

随机森林算法，很难得，用于数据分类效果比支持向量机算法效率高(Random Forest algorithm, it is difficult to get for data classification higher than the efficiency of support vector machine algorithm)

这是一个关于稀疏高斯过程的matlab源码，可以用于计算测试输入的高斯预测值。( spgp_pred computes the SPGP predictive distribution for a set of test inputs. You need to supply a set of pseudo-inputs or basis vectors for the approximation, and suitable hyperparameters for the covariance. You can use any method you like for finding the pseudo-inputs , with the simplest obviously being a random subset of the data. It is coded for Gaussian covariance function, but you could very easily alter this. It is also fine to use for high dimensional data sets. spgp_lik is the SPGP (negative) marginal likelihood and gradients with respect to pseudo-inputs and hyperparameters. So you can use this if you wish to try to optimize the positioning of pseudo-inputs and find good hyperparameters, before using spgp_pred . I would recommend initializing the pseudo-inputs on a random subset of the data, and initializing the hyperparameters sensibly. Its current limitations are that 1) it is slow and memory intensive for high dimensional data sets 2) it is heavi)

线性调频脉冲压缩的Matlab程序,有信道编码，调制，信道估计等，分析了该信号的时域、频域、倒谱，循环谱等。( LFM pulse compression of the Matlab program, Channel coding, modulation, channel estimation, Analysis of the signal time domain, frequency domain, cepstrum, cyclic spectrum, etc.)

2012和2013年关于北京天气统计用于功率负载等分析(related content u know)

由Jean-Francois Cardoso 提供的两个批处理的基于累积量的ica算法: JADE and SHIBBS (Jean-Francois Cardoso provided by the two batch algorithm based on the cumulative amount of ica: JADE and SHIBBS)

Algorithm Collections for Digital Signal Processing Applications Using Matlab.

deep learning一般是学习的层次结构，它也是有一定理论依据的，即模拟人脑的大脑皮层工作，因为大脑皮层的视觉区域也是分层次工作的，越底层的视觉皮层对那些底层特征就越敏感。综上所述，feature learning有这么多应用需求的驱动和生物神经理论上的支持，注定它能够在AI领域中发挥一定的作用。一些实验表明，有些feature learning学习到的特征几乎比所有其它的特征效果要好，比如本文中的ISA模型就是其中一个。(deep learning hierarchy of learning, it is also a certain theoretical basis that simulate the human brain' s cerebral cortex, visual areas of the cerebral cortex is hierarchical work, the more the bottom of the visual cortex is more sensitive to those underlying characteristics . In summary, feature learning so many application needs the support of the drive and biological neural theoretically doomed it to be able to play a certain role in the field of AI. Some experiments show that some feature learning learning to feature almost better than all the other features of the effect of the ISA model such as this is one.)

V2V simulation vehicle to vehicle communication(vehicle to vehicle communication based on random sourcing, urban & highway situation)