SpectralTools

good work on Pole placement method

4阶经典Runge-Kutta格式解常微分方程,Romberg(龙贝格）法求函数的积分,三阶样条插值（一阶导数边界条件）,定步长梯形法求函数的积分,矩阵A的伴随矩阵, Lagrange插值法数值求解,Newton迭代法解非线性方程f(x)=0(Fourth-order Runge-Kutta classic format solution of ordinary differential equations, Romberg (Romberg) method for function points, third-order spline interpolation (first derivative boundary conditions), fixed-step trapezoidal method for integrating functions, matrix A adjoint matrix, Lagrange interpolation method for numerical solution, Newton iterative method for solving nonlinear equations f (x) = 0)

ladder filter design package

觉得很好的一个Matlab程序想和大家一起分享，互相学习。(A Matlab program feel good and you want to share, learn from each other.)

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)

will be very useful for those who need code for lsb steganography

the attached utility is a work I ve submitted to the university It shows what a jpeg compression is all about. the function implements the DCT transform, using a matrix operator. note that matlab has a function for the DCT and iDCT transforms that might be more efficient.(the attached utility is a work I ve submitted to the universityIt shows what a jpeg compression is all about.the function implements the DCT transform, using a matrix operator.note that matlab has a function for the DCT and iDCT transforms that might be more efficient .)

SAR的点目标仿真 两点目标的回波仿真 两点目标距离向压缩 两点目标距离向和方位向压缩(SAR point target simulation two goals echo simulation two target range compression points to the distance and azimuth compression)

compressive sensing theory

用来计算无风险利率三次样条贴现函数的程序(No risk-free interest rate used to calculate the cubic spline function discounting)