ADM-LDM

说明：  本文在DCT噪声信号模型研究的基础上,提出了一种新的音频水印嵌入位置选择策略和一个应用该策略的自适应音频水印算法. 通过定义DCT系数的噪声敏感度,建立了水印嵌入位置和嵌入水印后的音频信号的听觉感知性之间的关系,根据音频水印的不可听性的要求选择最优的嵌入位置,然后调节水印强度来满足鲁棒性的要求,从而最大程度地保持音频水 印的不可听性和鲁棒性,为解决音频水印嵌入过程中不可听性和鲁棒性之间的矛盾提供了一种策略.(Though m any w orks in the literature agree that w aterm ark should be em bedded in the middle2fre2 quency coefficients or percep tually significant components, how to determ ine the position em bedded has no universal definition. A new em bedding strategy and an algorithm app lying the strategy are p roposed for audio w aterm arking in DCT dom ain based on research of DCT noise m odal. B y defining a noise sensitivity vector, a m ath relationship betw een the w aterm ark em beddable position and the audible quality of the audio file w ith w aterm ark is set up.)

Time-Series Prediction with NNMLP

这里的东西主要是SHELL的精馏塔的模型，欢迎大家下载使用。(The main thing here is the distillation column model SHELL, welcome to download.)

S 函数 编写的 最大功率捕获程序 在MATLAB上 调试成功 请大家参考(S function to write the greatest power capture program in MATLAB debugging success, please refer to)

water supply brancj system analyzer

短时傅里叶变换实现线性调频信号的时频分析(Time-frequency analysis of LFM signal by short time Fourier transform)

Syterm indentifitionf

support vector classification machine ％ soft margin ％ uses "kernel.m" ％ ％ xtrain: (Ltrain,N) with Ltrain: number of points N: dimension ％ ytrain: (Ltrain,1) containing class labels (-1 or +1) ％ xrun: (Lrun,N) with Lrun: number of points N: dimension ％ atrain: alpha coefficients (from svcm_train on xtrain and ytrain) ％ btrain: offest coefficient (from svcm_train on xtrain and ytrain) ％ ％ ypred: predicted y (Lrun,1) containing class labels (-1 or +1) ％ margin: (signed) separation from the separating hyperplane (Lrun,1(support vector machine classification% s oft margin% uses "kernel.m"%% xtrain : (Ltrain, N) with Ltrain : number of points N : % ytrain dimension : (Ltrain. 1) containing class labels (-1 or 1)% xrun : (Lrun, N) with Lrun : number of points N : % atrain dimension : alpha coefficients (from svcm_train on xtrain and ytrain)% btrain : offest coefficient (from svcm_train on xtrain and ytrain)%% ypred : predicted y (Lrun. 1) containing class labels (-1 or 1)% margin : (signed) separation from the separating hyper plane (Lrun, 1)

WENO SCHEME HYBRIDIZED WITH COMPACT SCHEME FOR EULER EQUATIONS

这个是tabu 搜索算法， 用matlab实现，有助于学习tabu算法的人(it is the TABU algorithm)