We will present the Newton-Raphson algorithm, and the secant method. A MATLAB function for the Newton-Raphson method. The function.MATLAB has many tools that make this package well suited for numerical computations. The Newton-Raphson method for systems of nonlinear equations.The Newton-Raphson method, or Newton Method, is a powerful technique. Interesting is Section 3, where the birth of the N...

The plain Newton-min algorithm to solve the linear complementarity problem (LCP for short) 0 6 x ⊥ (Mx + q) > 0 can be viewed as a semismooth Newton algorithm without globalization technique to solve the system of piecewise linear equations min(x,Mx + q) = 0, which is equivalent to the LCP. When M is an M-matrix of order n, the algorithm is known to converge in at most n iterations. We show in ...

In this paper, we present a modified regularized Newton method for the unconstrained nonconvex optimization by using trust region technique. We show that if the gradient and Hessian of the objective function are Lipschitz continuous, then the modified regularized Newton method (M-RNM) has a global convergence property. Numerical results show that the algorithm is very efficient.

A Newton method to solve total least squares problems for Toeplitz systems of equations is considered. When coupled with a bisection scheme, which is based on an eecient algorithm for factoring Toeplitz matrices, global convergence can be guaranteed. Circulant and approximate factorization preconditioners are proposed to speed convergence when a conjugate gradient method is used to solve linear...

The plain Newton-min algorithm to solve the linear complementarity problem (LCP for short) 0 6 x ⊥ (Mx + q) > 0 can be viewed as a semismooth Newton algorithm without globalization technique to solve the system of piecewise linear equations min(x,Mx + q) = 0, which is equivalent to the LCP. When M is an M-matrix of order n, the algorithm is known to converge in at most n iterations. We show in ...

We show how the method of pseudo-transient continuation can be applied to improve the robustness of the Newton iteration within a nonlinear transient elasticity simulation. Pseudotransient continuation improves efficiency and robustness of the transient analysis by enabling larger time steps than possible with a Newton iteration. We illustrate the algorithm by reporting on a simulation of a buc...

A Newton method to solve total least squares problems for Toeplitz systems of equations is considered. When coupled with a bisection scheme, which is based on an eecient algorithm for factoring Toeplitz matrices, global convergence can be guaranteed. Circulant and approximate factorization preconditioners are proposed to speed convergence when a conjugate gradient method is used to solve linear...

Optimization plays a key role in machine learning. Recently, stochastic second-order methods have attracted much attention due to their low computational cost in each iteration. However, these algorithms might perform poorly especially if it is hard to approximate the Hessian well and efficiently. As far as we know, there is no effective way to handle this problem. In this paper, we resort to N...

In the Newton/log-barriermethod,Newton steps are taken for the log-barrier function for a xed value of the barrier parameter until a certain convergence criterion is satis ed. The barrier parameter is then decreased and the Newton process is repeated. A naive analysis indicates that Newton's method does not exhibit superlinear convergence to the minimizer of each instance of the log-barrier fun...

A novel type of fractals (i.e., Zhang fractals) is yielded via solving time-varying or static nonlinear equations in complex domain by discrete-time complex-valued Zhang dynamics (DTCVZD). The DTCVZD model that uses different types of activation functions can generate various Zhang fractals. These fractals are different from the conventional Newton fractals discovered 30 years ago (since 1983) ...