LTE-SAE-Model-and-its-Implementation-in-NS-2

Navigation bar example

speech recognition, butterworth filter

The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order (The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order)

this is simple sample of ART neural network: main file: ART.m

小波包进行信号去噪的m文件，在matlab中可以直接调用(Wavelet packet signal de-noising m file in matlab can be called directly)

本Matlab程序对脑区域图像进行分析，计算脑体积。(The Matlab program to analyze images of brain regions, calculated brain volume.)

finite-time稳定控制算法，李雅普诺夫方法得出LMI算法，进而求出反馈增益矩阵(finite-time stability control algorithm)

说明：  直接带入数据..可以求解理论总塔板数以及提馏和精馏段塔板数(directly into the data can be solved .. Theory total plate number and stripper and distillation of the plate numbers)

A Guide to MATLAB Object Oriented Programming

genetic algorithm tool box