lianxu

说明：  加信噪声，单边带调幅，设计波特滤波器，过滤噪声，比较经过希尔伯特变换前后的区别(Plus letter noise, single-sideband amplitude modulation design Potter filters, filter noise comparison, after the difference between before and after the Hilbert transform)

将宽频带系统的输出仿真到窄频带输出的方法。(Broad-band system will be output to a narrow band output simulation approach.)

车间作业调度问题Matlab源码,用于完成车间作业的最优化调度(Job Shop Scheduling Problem Matlab source code for the completion of Job Shop Scheduling Optimization)

这个程序是用来显示经过经验模态分解后所得的各个固有模态函数和残余信号，以及由它们重建的信号。(This procedure is used to show through after EMD from various intrinsic mode function and the residual signal, as well as the reconstruction of the signal from them.)

说明：  OFDM水声通信中最大多普勒频偏估计算法研究(OFDM underwater acoustic communication in the largest Doppler shift estimation algorithm)

说明：  因此，本文在分析IEEE 802.16标准和WiMAX网络架构的基础上，研究基于 WiMAX技术宽带无线网络下的切换策略，以提高WiMAX系统的性能。 (the first stage. Based on the analysis of IEEE 802.16 standard and AMAX network architecture, the handover mechanism for broadband wireless network based on AMAX technology is studied in this thesis, for the purpose of improving the performance of WiMAX systems )

说明：  含有噪声的余弦序列，分别采用周‘期图法’与‘改进协方差法’估计序的功率谱(Contain noise cosine sequence, were used weeks period diagram with the improved covariance method estimates the power spectral sequence)

MATLAB平台下的基于人工神经网络的非线性控制系统PID参数整定代码，能实现在线调节功能。(MATLAB platform artificial neural network-based nonlinear control system PID parameter tuning code, to achieve regulatory function online.)

企业信息交流系统(CICS)为企事业提供最新的资讯(Enterprise information exchange system (CICS) for the enterprises and institutions to provide the latest information)

当信噪比较大时，采用广义最小二乘法可能会出现多个局部收敛点，解决这个问题的方法可用多级最小二乘法，一般来说多级最小二乘法包含三级辨识过程。利用输入输出数据，通过多级最小二乘法，可分别求的辅助模型，过程模型和噪声模型的参数估计值。在高噪声的情况下，多级最小二乘法明显优于广义最小二乘法，其收敛点唯一。(When the signal noise ratio (SNR), and by use of the generalized least squares method may appear more local convergence point, the way of solving this problem can be used multistage least squares method, and generally multistage least squares method includes three identification process. Using input/output data, through the multistage least squares, respectively for the auxiliary model, process model and noise model parameter estimation. In the high noise, multistage least squares method is obviously superior to the generalized least squares method, and its convergence point only.)